A Complete Bibliography of Publications in Biometrika for the decade 2020–2029

Nelson H. F. Beebe University of Utah Department of Mathematics, 110 LCB 155 S 1400 E RM 233 Salt Lake City, UT 84112-0090 USA

Tel: +1 801 581 5254 FAX: +1 801 581 4148

       E-mail: beebe@math.utah.edu, beebe@acm.org,
                  beebe@computer.org (Internet)
     WWW URL: https://www.math.utah.edu/~beebe/

13 October 2023 Version 1.11

Title word cross-reference

F [KZ23]. K [PSCW20, MW20]. p [GLS21, VW20].

-modelling-based [KZ23]. -nearest [PSCW20]. -sample [MW20]. -values [VW20].

aberration [TX22]. aberration-type [TX22]. abundance [Wan23]. accuracy [BDS22, JA20]. accurate [FDZ22]. acyclic [LLFT22]. Adaptive [AVCG20, PSCW20, GLS21, JA20, LTM23, PEAL21, YYS22, ZZC21]. Additive [LMP23, HNS21]. adjusted [LY20, LTM23, Zha22b]. Adjusting [ST22a]. adjustment [GPR^{+}23a, LD21, SSR22]. adjusts [WA23]. Admissible [MS21]. adversarial [COF20]. algorithm [DJ20, GD22, LS23a, XL22]. algorithms [AAR21, SWU21, VLZ23]. always [BPR20]. analysi [BM21, Bub21, CO21, GGH^{+}21b]. Analysis [LGR20, CTGS22, DS21, GGH^{+}21a, LZW23, MT21, MZ22, PAJ22, QLR23, SZZ22, SYY21, WJ22, YCG20, ZC21]. Ancestor [Ano23a, SB23]. ANOVA [SZM21]. application [BUCFFH21, JLM21, THT^{+}23]. applications [NKK21, SZZ22]. approach [Mao20, MW20, WPTC20, WPS22]. approximate [CRRS21, VF20, WX22]. approximately [WZ20]. Approximating [vdBRD21, vdBRD22]. approximation [LD20, MZZ^{+}20, Woo20, vdBRD21, vdBRD22]. arbitrary [WX22]. area [Sug20]. arrays [MFM23]. Assessing [AVH21, SWD23]. assessment [DDH^{+}23]. assisted [ST22a]. association [WL22, ZZC21]. associations [LSR^{+}22]. assumption [KM20, LB21]. assumption-free [LB21]. assumptions [LS23b]. Asymptotic [SC22, MB21, SZM21, WZ20]. Asymptotics [Zha22a, MO21, SDDP21]. attraction [EBMVZ22]. augmentation [LL21]. autocorrelations [Zha22a]. autocovariances [CCY22]. autoregressive [Muk20, ZC21]. Average [HLW22, LY20, VF22, YYS22]. averaging [VW20]. aware [DNC22, HMvB21].

Backfitting [MS22a, HNS21]. bacterial [CZL20, MCL21]. Bagging [BUCFFH21]. balanced [VLZ23]. balancing [NSI20, WZ20]. bandwidth [MO21]. bandwidths [BUCFFH21]. Barker [VLZ23]. based [CCY22, CV23, He21, Kon20, KZ23, LLLD23, MCL21, QLR23, SWU21, XL22, ZJB21, ZD22]. bases [HMvB21]. Basis [LWZ21, MZZ^{+}20]. Bayes [FDZ22, KZ23, RHD23, Sug20, WPS22]. Bayesian [CBM20, CRRS21, DYND20, GLS21, LDD20, MCFB22, SK22, SSYL20, VF20, XX20, YGT20]. Behrens [WX22]. Benjamini [ST22a]. Bernoulli [VGLR22]. best [HHLL23]. best-subset [HHLL23]. between [YZ23]. beyond [FN22, TZ22]. bias [Ros20, RSR21, THT^{+}23]. big [BUCFFH21, WM21]. binary [DDH^{+}23, FDZ22, GRR21, JD20, KCB^{+}21, KYW22, KBLM23, QYK^{+}21a, QYK^{+}21b, WZRR21, ZL21b]. binomial [KF21]. binomial-response [KF21]. Bio [DK21]. Bio-equivalence [DK21]. biomarkers [SZW21]. blind [BGN^{+}20]. Block [KLY21, ZJB21]. boosting [LH23]. bootstrap [GMR20, KLY21]. Bootstrapping [KP23, Muk20]. bouncy [ST22b]. bounds [PC22]. brain [NKK21]. breakpoint [Che21].

calculation [Mao20]. calibrated [Tan20]. calibration [DDH^{+}23]. canonical [MZ22, YCG20]. Carlo [GLS21, HJ20, LWDL22, LS23a, NDL20, SSYL20, VGLR22, VF20]. case [YMRW22]. causal [BDT23, CZ23, CTGS22, DHRvDL21, GRR21, HLW22, KCB^{+}21, KYW22, NSI20, QYK^{+}21a, QYK^{+}21b, RR23, SWD23, SSR22, SWU21, WD20, ZL21b, ZD22]. causes [KYW22, LGL^{+}23]. censored [XZL23]. censoring [BKGF20, CHCK23, CV23, DV21a, DV22]. chain [GLS21, LS23a, SSYL20, VGLR22, VF20]. Changepoint [YHF21, KBLM23, SC22]. characteristic [AVH21]. Characterization [RSR21]. Chatterjee [LH23, SDH22]. class [LGL20]. Classification [CFS20, LD20]. closed [Dob20]. cluster [LLLD23, SWD23]. cluster-level [SWD23]. Clustering [ALRZ23, FI23, RHD23]. coefficients [NS22]. column [Ano23b, ZZ23]. Combining [VW20]. communication [DNC22, Sen22]. communication-efficient [DNC22]. community [LCL20]. compact [DRS23]. comparison [MW20]. competing [BKGF20]. completely [LD21]. complexity [FK21]. component [QLR23]. Componentwise [CRRS21]. Composite [PEAL21, HNRC20]. composition [CZL20, WCL21]. compositional [SZZ22, Wan23]. computation [CRRS21, VF20]. computer [PEAL21]. concentration [RC20]. concomitant [FI23]. conditional [GR20, LZS20, LKJR22, Muk20, PGDM20, Ros20, TZ22, WJ22]. Confidence [BMS22, Zha22b]. conformal [Gua23]. confounders [DHRvDL21]. confounding [CTGS22, GPR^{+}23a, MSK^{+}20]. conjugate [LGR20]. connectivity [NKK21]. considerations [WZ20]. Consistency [GMR20, SWU21, ALRZ23]. Consistent [LCL20]. constrained [AVCG20, THT^{+}23]. constraint [DYND20]. constraints [LRF21]. constructing [LLT21]. contamination [LY21]. continuous [Gun21, YPC20]. continuous-time [YPC20]. contraction [JG21]. control [LRF21, NS22, SKN^{+}22, ZZC21]. controlling [ST22a]. copulas [CV23]. Correction [Ano23a, Ano23b, DV22, HZ22a, LW20, vdBRD22, VF20]. correlation [LH23, MZ22, SK22, SCHL23, SDH22, WL22, YCG20]. correlation-shrinkage [SK22]. cost [WCL21]. count [ZL21a]. counting [SCMH22]. couplings [HJ20]. covariance [GT21, MSP23, MC22, VF22, XL22, YXZ23]. covariances [Gui22, WX22]. Covariate [ZZC21, LTM23, NSI20, YYS22]. covariate-adaptive [LTM23, YYS22]. covariates [COW22, LD21, TZ22, YHF21, ZLWL22]. coverage [Zha22b]. Cox [CMTT23]. criterion [Hui21, TX22]. critical [AVCG20]. cross [BUCFFH21, CKY20, FH20, GM20, HDL20, LL20, LLZ20a, LLZ20b]. cross-sectional [HDL20]. cross-validated [BUCFFH21]. cross-validation [CKY20, FH20, GM20, LL20, LLZ20a, LLZ20b]. crossed [PRZ20]. cumulative [LDD20]. cure [AVH21, EBMVZ22]. curves [AVH21].

Data [TCH23, AVH21, BUCFFH21, BM21, BPR20, Bub21, CZL20, CO21, DS21, DV21a, DV22, DK21, DDB22, GGH^{+}21a, GGH^{+}21b, HDL20, JLM21, KLY21, LGR20, LZS20, LCL20, SZZ22, SC22, Tan20, WM21, Wan23, XZL23, YCG20, YXZ23, ZL21a, ZDS^{+}20, ZXZ22, ZLWL22, ZYZ23]. debiased [CNS23]. Decomposition [XC22]. decrease [BDS22]. definite [LMP23]. demonstrated [Ros20]. Demystifying [LGL20]. density [PGDM20, Sug20]. dependence [GM22a, SWT20, Ber22, GM22b, LEZK^{+}22, SJS^{+}22]. Dependent [CV23, CHCK23, DV21a, DV22, KLY21, Zha21, Zha22a]. Design [LLLD23, Ano23b, HP21, LB21, RR23, VLZ23, ZD22]. Design-based [LLLD23, ZD22]. designs [Azr23, BDT23, He21, LLT21, PEAL21, TX22, ZZ23]. detection [DFW20, FI23, KBLM23, LCL20, SC22]. determination [LL21]. Determining [CL22, SWT20]. deviation [DK21]. Diagnosing [BPR20]. differential [NKK21, Wan23]. Dimension [ZLWL22, YZ23, YY22, ZZZ21]. dimension-and-sample [YZ23]. dimensional [CCTW21, CL22, CLC23, CLYZ20, DV21b, FDZ22, GT21, HHLL23, KKSC23, LZW23, LXYY22, MO21, MW20, NSI20, SK22, SSLD20, SZZ22, Tan20, WD20, WX22, WJ22, YXZ23, ZB22, ZXZ22, ZYH22, ZWZ20, vdBRD21, vdBRD22]. dimensions [MZ22, QQJG20, YZ23]. direct [HLW22]. directed [LLFT22]. Dirichlet [ALRZ23]. Discontinuous [NDL20]. discovery [LRF21, MCFB22, ST22a, WD20]. discrepancy [YZ23]. discrete [LS23a, NDL20, ST22b]. discrete-time [LS23a]. discretely [ZYZ23]. discriminant [PAJ22]. Discussion [Ber22, BM21, Bub21, CKY20, CO21, GM20, GRR21, KCB^{+}21, LEZK^{+}22, LL20, SJS^{+}22, ZL21b]. dispersion [WZ20]. distance [He21, LLT21, XL22]. distillation [LKJR22]. Distributed [CLZ22, DNC22]. Distribution [GP22, MB21, NBP20, SC22, ZS22]. distribution-free [SC22]. Distribution-on-distribution [GP22]. distributionally [BMS22]. distributions [EBMVZ22, HMF22]. divergence [Sug20]. divergent [TZ22]. diverging [LD21]. domain [EBMVZ22]. dose [ZZZ21]. dose-finding [ZZZ21]. dot [XX20]. Doubly [QQJG20]. driven [GMR20]. dynamic [CHCK23, HMvB21, SYY21]. dynamical [SZW21].

edge [CKY20, GM20, LL20, LLZ20a, LLZ20b]. effect [DV21b, LY20, LTM23, MSK^{+}20, SWD23, WPTC20, YYS22, YMRW22, ZWZ20]. effects [BDT23, CTGS22, GRR21, HLW22, KCB^{+}21, KYW22, LGL^{+}23, NS22, NW21, NSI20, PRZ20, PK22, QYK^{+}21a, QYK^{+}21b, RR23, WZRR21, XC22, ZL21b]. efficiency [Che21, Mao22, Sen22]. Efficient [PK22, SSLD20, SSR22, VGLR22, DHRvDL21, DNC22, GPR23b, MZZ^{+}20]. eigenvalues [TY20]. elicitable [HMF22]. Elicitation [FK21]. elimination [GPR23b]. Empirical [CLYZ20, CCTW21, KLY21, KZ23, MO21, Sug20, SZM21, WPS22, YGT20]. Ensemble [SLCF20]. Envelopes [ZLS20]. environment [LSR^{+}22]. equation [Ano23a, SB23]. equivalence [DK21]. Erratum [Ano22]. error [BPBS21, DS21, FY21, LZF20, NBP20, SZZ22, ZZC21]. errors [JD20, LB21, NBP20]. errors-in-variables [NBP20]. essential [LMSW20]. estimands [ZD22]. estimates [LY20, TCH23]. Estimating [NKK21, QYK^{+}21a, VF22, GRR21, KCB^{+}21, QYK^{+}21b, ZL21b]. Estimation [EBMVZ22, HDL20, LZF20, MS22b, NBP20, WZRR21, WL22, ZWZ20, BMS22, CZL20, COW22, Che21, CTGS22, CMTT23, DV21a, DV22, KZ23, LW18, LW20, LTM23, MCL21, MSP23, MSK^{+}20, NW21, NSI20, PK22, PGDM20, SCHL23, SLCF20, Sug20, Tan20, XC22, XX20, XL22, YPC20, ZL21a]. estimator [Kon20, ZS22]. estimators [Azr23, KP23, LGL20, MS21, Muk20]. Evaluating [LGL^{+}23]. evaluation [YHF21]. Event [BM21, Bub21, CO21, GGH^{+}21a, GGH^{+}21b, SYY21]. events [MPHF21]. exact [LB21, SKN^{+}22]. excess [HNS21]. exchangeable [Dob20, LB21, MFM23]. excursion [GRR21, KCB^{+}21, QYK^{+}21a, QYK^{+}21b, ZL21b]. Existence [DRS23]. expansions [LWZ21, MSP23]. experiments [BDT23, LD21, LY20, PEAL21, ZD22]. explained [WPTC20]. exploiting [TCH23]. exponentially [YGT20]. Extended [SSYL20]. extensions [QLR23]. external [TCH23, ZDS^{+}20]. extreme [CLZ22, ZS22]. extremes [FI23, SWT20].

factor [CL22, HZ22c]. factorial [ZD22]. factorization [SCD22]. factorizations [LDD20]. factors [CL22, Kon20]. factory [VGLR22]. failure [YPC20]. false [LRF21, ST22a, Zha22b]. familywise [ZZC21]. Fast [Dob20, LKJR22, KBLM23, PEAL21]. fifty [DJ20]. filling [MZZ^{+}20, TX22]. filter [GD22, LW18, LW20, LSR^{+}22, Sen22]. filtering [PC22]. finding [ZZZ21]. Finite [ZC21, CNS23]. finite-sample [CNS23]. Finite-time [ZC21]. finiteness [KF21]. Fisher [Ber22, GM22b, LEZK^{+}22, SJS^{+}22, GM22a, WX22]. fixed [LB21]. fixed-design [LB21]. flow [WCL21]. follow [EBMVZ22]. follow-up [EBMVZ22]. forecast [HZ22a, HZ22b]. forecasting [LXYY22]. forests [BDS22]. forms [BZ21]. formula [GPR23b]. framework [Gua23, LRF21, RHD23]. Fréchet [YY22]. free [LB21, SC22, WPTC20]. function [FN22]. Functional [HZ22c, LY21, ZYZ23, DK21, LZS20, LWZ21, PAJ22, QQJG20, ZOP22]. functionals [SKN^{+}22]. fused [PSCW20].

g [GPR23b]. g-formula [GPR23b]. game [COF20]. Gauss [JA20]. Gaussian [vdBRD22, DDB22, DRBW23, KKSC23, PGDM20, ZOP22, vdBRD21]. Gaussianity [WD20]. General [BKGF20, Zha22b, CNS23, HP21, KBLM23, LRF21, YMRW22]. Generalized [KM20, SCD22, ZDS^{+}20, BZ21, CL22, CLC23, DFBL22, Gua23, Hui21, JG21, KF21, LGR20, MS22a, Muk20, RHD23, ZS22]. genetic [WL22]. genome [ZZC21]. genome-wide [ZZC21]. genomic [MCFB22]. Geometrically [HMvB21]. Gibbs [CRRS21]. Gibbs-like [CRRS21]. global [GD22, ZS22]. Gradient [QLR23, SSYL20]. Gradient-based [QLR23]. graph [GPR23b]. Graphical [DDB22, KKSC23, NKK21, QQJG20, SSR22, WA23, ZOP22]. graphon [COW22]. graphons [LS23b]. graphs [LLFT22, RC20, XX20]. greedy [SWU21]. grid [PEAL21]. grids [Gui22]. grouped [LGR20]. groups [FI23, LMP23]. growth [MCL21]. guarantees [CNS23, SWU21]. Gumbel [EBMVZ22].

habituation [BDT23]. Hamiltonian [HJ20, NDL20]. handling [HZ22c]. Hastings [DJ20, VLZ23]. hazards [XZL23]. health [GRR21, KCB^{+}21, QYK^{+}21a, QYK^{+}21b, ZL21b]. Hermite [JA20]. Heterogeneity [DNC22, HZ22c, SWD23]. Heterogeneity-aware [DNC22].

Heterogeneous [MPHF21, NS22, NW21]. heteroscedastic [Muk20]. heteroscedasticity [ZLS20]. hidden [SSR22]. High [CCTW21, LZW23, SZZ22, WD20, Zha21, ZB22, ZYH22, CL22, CLC23, DV21b, FDZ22, GT21, HHLL23, KKSC23, LXYY22, MO21, MZ22, MW20, NSI20, QQJG20, SSLD20, Tan20, WX22, WJ22, YZ23, YXZ23, ZXZ22, ZWZ20, vdBRD21, vdBRD22]. High-dimensional [CCTW21, LZW23, SZZ22, WD20, ZB22, ZYH22, CL22, CLC23, DV21b, FDZ22, GT21, HHLL23, KKSC23, LXYY22, MO21, MW20, NSI20, SSLD20, Tan20, WX22, WJ22, YXZ23, ZXZ22, ZWZ20, vdBRD21, vdBRD22]. High-quantile [Zha21]. highly [DDB22]. histogram [LMSW20]. history [BM21, Bub21, CO21, GGH^{+}21a, GGH^{+}21b, SYY21]. Hochberg [ST22a]. Honest [DDH^{+}23, KBW23]. hop [LS23a]. Hug [LS23a]. hybrid [HZ22c]. hyperbolic [BZ21]. Hypotheses [BPBS21]. Hypothesis [WCL21].

ideal [ZYZ23]. Identifiability [KYW22]. identification [NS22, THT^{+}23, XC22]. imaging [HZ22c]. imbalanced [SSLD20]. imperfect [CFS20]. implicit [ZYH22]. implied [CZ23]. improve [Zha22b]. improved [ZDS^{+}20]. inconsistency [BDS22, Säv22]. independence [Ber22, GM22a, GM22b, GR20, KM20, LZS20, LEZK^{+}22, MC22, SJS^{+}22]. index [CLZ22]. indexes [SCMH22]. indirect [HLW22, ZWZ20]. individual [MPHF21]. inequalities [KM20]. inexact [GR23]. Inference [DV21b, YYS22, YGT20, CCTW21, CZ23, CLZ22, DV21a, DV22, DNC22, Gua23, HZ22a, HZ22b, HNRC20, KKSC23, KBW23, PRZ20, PEAL21, RY23, SWU21, SCMH22, WPS22, YHF21, ZDS^{+}20, ZB22, ZD22, ZWZ20]. infinite [LDD20, SCD22]. inflated [VF20, YLYG23]. information [Hui21, Mao20]. inner [MSP23]. insensitivity [Ros20]. instrument [Gun21]. Instrumental [CMTT23, JD20, KM20, WZRR21]. insufficient [EBMVZ22]. Integrated [TZ22, Woo20, vdBRD21, vdBRD22]. integration [TCH23, ZDS^{+}20]. intent [Mao22]. intent-to-treat [Mao22]. interactive [LRF21]. interference [HLW22, PK22, SWD23]. intermediate [DHRvDL21]. interplay [YZ23]. Interpoint [MC22]. Interpoint-ranking [MC22]. interval [XZL23]. interval-censored [XZL23]. intervals [Zha22b]. intractable [VGLR22]. Inverse [LXYY22, HMvB21]. Inverses [Gui22].

Jackknife [MO21]. Jeffreys [KF21]. Jeffreys-prior [KF21]. Joint [ZXZ22]. Jump [Che21].

Kernel [YZ23]. kink [Che21]. knockoff [LSR^{+}22, ST22a]. knockoff-assisted [ST22a]. knockoffs [WJ22]. Kronecker [YXZ23].

labels [CFS20]. lag [VF22]. Laplace [Woo20]. Large [DFBL22, SDDP21, CLYZ20, GLS21, SSYL20, SZM21]. large-dimensional [CLYZ20]. Large-sample [SDDP21]. Large-scale [DFBL22, SSYL20]. Lasso [LTM23, PSCW20, WA23]. Lasso-adjusted [LTM23]. Lassoing [TY20]. Latent [MLZ22, CL22, NKK21, WA23, ZXZ22]. Lattice [He21]. Lattice-based [He21]. layer [LCL20]. Learning [ZJB21, CNS23, QLR23, ZB22]. least [Azr23]. left [BKGF20]. left-truncation [BKGF20]. less [MCFB22]. level [SWD23]. leveraging [ZDS^{+}20]. Lie [LMP23]. like [CRRS21]. likelihood [AVCG20, CCTW21, CLYZ20, DRBW23, FH20, HNRC20, MO21, MT21, XL22, YGT20, ZL21a, ZS22]. likelihood-based [XL22]. likelihoods [NDL20]. limited [Sen22]. linear [Ano23a, COW22, CZ23, Che21, CLC23, DFBL22, FN22, HMvB21, Hui21, JG21, KF21, LGR20, LB21, LZW23, NBP20, PAJ22, SB23, ZYH22, ZC21, ZWZ20, ZYZ23]. Linearized [SCHL23]. Local [COW22, Dob20, FN22, LD20, WZRR21]. Localized [Gua23]. locally [VLZ23]. log [SZZ22]. log-error-in-variable [SZZ22]. logistic [FY21, PGDM20, SSLD20]. loss [MS22b]. lost [GLS21]. Lugsail [VF22].

M [Muk20]. M-estimators [Muk20]. machine [CNS23]. manifold [LD20, LY21]. Mann [Mao22]. maps [GP22]. Marginal [XZL23, CTGS22, CMTT23, FH20, GR20, SDDP21]. marker [WPTC20]. Markov [GLS21, HMvB21, LS23a, SSYL20, VGLR22, VF20]. matched [COF20, Ros20]. matching [DRS23, GR23, MT21, Säv22]. Matérn [Gui22]. matrices [CZL20, LMP23, VF22, YXZ23, ZJB21]. Matrix [FY21, MCL21, MS22b, YXZ23]. Matrix-variate [FY21, YXZ23]. maximin [LLT21]. maximizing [MCFB22]. Maximum [ZL21a, DK21, EBMVZ22, SCHL23, ZS22]. MDA [BDS22]. Mean [BDS22, CLYZ20, LZS20, MS21, YLYG23, ZB22]. Measurement [JD20, DS21, FY21]. Median [KBW23]. mediation [DHRvDL21, XC22, ZWZ20]. mediator [MSK^{+}20]. mediator-outcome [MSK^{+}20]. mediators [XC22]. metagenomics [CZL20]. method [DFW20, LLT21, ST22a, SDDP21, SKN^{+}22, SZM21]. methodology [KBLM23]. methods [LXYY22, YYS22]. Metropolis [VLZ23]. microbial [SZZ22]. Minimal [WZ20, LS23b]. Minimax [BDT23, Azr23]. minimization [YYS22]. minimum [TX22, WCL21]. minimum-cost [WCL21]. Missing [FDS22, BPR20, YHF21]. misspecification [Tan20]. misspecified [DFBL22, DV21b]. mixed [Hui21, LGR20, RSR21, YCG20]. mixing [GLS21]. mixture [LPR20]. mixtures [ALRZ23]. mobile [GRR21, KCB^{+}21, QYK^{+}21a, QYK^{+}21b, ZL21b]. mode [HMF22]. Model [WPTC20, Ano23a, BKGF20, CMTT23, DFBL22, HDL20, HNS21, HZ22c, JD20, PGDM20, SK22, Tan20, TCH23, WZRR21, YLYG23, ZDS^{+}20, ZD22, ZZZ21]. Model-free [WPTC20]. Modelling [SZW21, DV21a, DV22, KZ23, LPR20, MPHF21, YMRW22]. models [CL22, CLC23, DFBL22, DDB22, DV21b, FDZ22, GT21, Hui21, JLM21, JG21, KKSC23, KF21, LGR20, LB21, LMP23, MLZ22, MS22a, Mao20, Muk20, NKK21, NBP20, PRZ20, QQJG20, SCD22, SB23, SLCF20, SSR22, SZM21, XZL23, YPC20, ZOP22, ZL21a, ZLS20, ZXZ22, ZC21, ZWZ20]. moderation [SWD23]. modularity [MB21]. moment [LXYY22, TZ22, YZ23]. monotone [MCL21]. Monte [NDL20, GLS21, HJ20, LWDL22, LS23a, SSYL20, VGLR22, VF20]. Multi [CHCK23, GM22a, LCL20, LSR^{+}22, Ber22, GM22b, LEZK^{+}22, SJS^{+}22]. multi-environment [LSR^{+}22]. multi-layer [LCL20]. Multi-scale [GM22a, Ber22, GM22b, LEZK^{+}22, SJS^{+}22]. Multi-stage [CHCK23]. multinomial [LPR20]. multiple [CBM20, KYW22, NS22, XC22]. multiplex [MLZ22]. Multiplicative [YMRW22, YLYG23]. multiply [LGL20, XC22]. Multisample [CZL20]. Multivariate [COF20, Ber22, BPR20, BZ21, CG22, DDB22, GM22a, GM22b, HHLL23, LEZK^{+}22, LZW23, MS21, SJS^{+}22, SWT20, XZL23, ZOP22, ZLS20].

natural [XC22]. nearest [PSCW20]. neighbour [PSCW20]. nested [LLFT22, Woo20, YLYG23]. Network [LLZ20a, LCL20, MO21, PK22, ZXZ22, ZLWL22, CKY20, GM20, LL20, LLZ20b]. networks [MB21, MLZ22, SYY21]. node [ZXZ22]. non [WD20]. non-Gaussianity [WD20]. noncompliance [Mao22]. nonlinear [SZW21]. nonlinearity [ZLS20]. Nonparametric [DHRvDL21, MW20, PSCW20, WPS22]. nonparametrics [MCFB22]. nonreversible [LS23a]. Nonsmooth [HNS21]. Nontestability [Gun21]. normal [MS21]. note [JA20]. nuisance [CLC23, vdBRD21, vdBRD22]. number [CL22, Kon20, LD21, TZ22].

objects [YY22]. observational [COF20, GR23, Ros20, RR23]. observations [SC22]. observed [ZYZ23]. one [COF20]. one-sided [COF20]. online [QLR23]. operating [AVH21]. operators [Mao20]. Optimal [Ano23b, Azr23, MCL21, VLZ23, WM21, WPS22, XX20, ZZ23, CHCK23, GP22, He21, KBLM23, LWDL22, ZB22]. optimality [KLY21, ZS22]. optimization [GD22]. oracle [NW21]. order [LL21]. orders [YZ23]. other [VLZ23, YYS22]. outcome [DDH^{+}23, KYW22, MSK^{+}20]. outcomes [CHCK23, QYK^{+}21a, YLYG23, GRR21, KCB^{+}21, QYK^{+}21b, ZL21b].

panel [ZL21a]. paradata [DS21]. parameter [TCH23]. parameters [CLC23, DV21b, NDL20, RSR21, SZM21, vdBRD21, vdBRD22]. parametric [CV23]. parsimonious [ZZZ21]. Partial [ZOP22, MSP23, PK22, THT^{+}23]. Particle [Sen22, GD22, LW18, LW20, ST22b]. partition [PGDM20]. Path [RC20, MSK^{+}20]. path-specific [MSK^{+}20]. penalized [Hui21]. penalty [KF21]. performance [HZ22a, HZ22b]. permutation [SWU21]. permutation-based [SWU21]. permuted [MCL21]. personalized [ZZZ21]. perspective [FDS22, WCL21]. perturbation [Kon20]. phase [HMZX21, Zha22a]. phenomenon [HMZX21]. phylogenetic [WCL21]. Pitman [LPR20]. point [CG22]. Poisson [JLM21]. political [JLM21]. positive [LMP23]. positive-definite [LMP23]. post [RY23, VF20, WPS22]. post-correction [VF20]. post-selection [RY23, WPS22]. Posterior [JG21, LGL^{+}23, SSLD20]. posteriors [VGLR22, vdBRD21, vdBRD22]. potentially [DV21b]. power [LH23, SDH22, Sug20, WJ22]. powerful [LKJR22]. practical [BDS22, WZ20]. predicting [MCFB22]. prediction [AVH21, Gua23, SK22]. predictions [DDH^{+}23]. predictor [LL21]. predictors [LXYY22]. presence [Mao22, MSK^{+}20, SWD23, YHF21]. principal [QLR23, YHF21]. prior [KF21, SK22]. priors [DRS23]. probabilistic [RHD23]. probability [HZ22a, HZ22b, YGT20]. problem [WX22]. problems [HMvB21, MW20]. process [ALRZ23, DDB22, FDS22, LPR20]. processes [CG22, PGDM20, SCMH22, YPC20, ZOP22]. product [MSP23, XX20, YXZ23]. projections [He21]. Propensity [RR23, NSI20, Tan20]. properties [AAR21, FK21, WZ20, ZD22]. property [RSR21]. proportion [WPTC20]. proportional [XZL23]. proposal [VLZ23]. proximal [XL22]. pseudo [SDDP21]. pseudo-marginal [SDDP21].

quadratic [BZ21, MS22b]. quadrature [JA20]. quantifying [WPTC20]. quantile [MT21, PC22, WM21, Zha21]. quantile-matching [MT21]. quantiles [KLY21]. Quasi [NW21, He21]. quasi-optimal [He21]. Quasi-oracle [NW21]. quasilikelihood [Hui21].

random [Azr23, BDS22, BPR20, BZ21, FDS22, Kon20, PRZ20, XX20, YY22]. random-perturbation-based [Kon20]. randomization [LKJR22, LTM23, WX22, WJ22, YYS22]. randomized [LD21, LY20]. rank [CBM20, HP21, JLM21, Kon20, LH23, SCHL23, SDH22]. ranking [MC22]. rate [EBMVZ22, LRF21, ST22a, Zha22b, ZZC21]. rate-adjusted [Zha22b]. rates [BPBS21, MCL21]. ratio [AVCG20, DRBW23]. ratios [TCH23]. reality [ZYZ23]. receiver [AVH21]. recurrent [MPHF21]. reduced [JLM21, TCH23]. reduced-rank [JLM21]. reduction [CBM20, GPR23b, YY22, ZLWL22, ZZZ21]. regimes [CHCK23]. regions [BMS22]. Regression [LD21, LY20, MFM23, ZD22, Ano23a, BKGF20, CBM20, CZ23, Che21, FY21, FDZ22, FN22, GP22, HNS21, HHLL23, HZ22c, LY21, LZF20, LZW23, PSCW20, SB23, SSLD20, SZZ22, SLCF20, WM21, ZL21a, ZLS20, Zha21, ZYH22, ZYZ23]. Regression-adjusted [LY20]. Regression-based [ZD22]. regularity [KBW23]. regularization [ZYH22]. Regularized [Tan20]. Rejoinder [GGH^{+}21b, GM22b, LLZ20b, QYK^{+}21b]. relational [MFM23]. relative [HMF22, Mao22]. relaxation [DYND20]. repeated [SC22]. replacement [Säv22]. rerandomization [LLLD23]. resampling [LWDL22]. respondent [GMR20]. respondent-driven [GMR20]. Response [HHLL23, KF21]. restrictions [ZC21]. ridge [LZF20]. right [BKGF20]. right-censoring [BKGF20]. Risk [PC22, BKGF20, HNS21, MPHF21]. Robust [NSI20, Sug20, Wan23, BMS22, DFW20, LGL20, LSR^{+}22, XC22]. role [GR23]. roots [CCY22]. rotated [vdBRD21, vdBRD22]. row [Ano23b, ZZ23]. row-column [Ano23b, ZZ23].

Sample [THT^{+}23, CCY22, CNS23, KLY21, MW20, SDDP21, WX22, YZ23, Zha22a]. Sample-constrained [THT^{+}23]. sampler [ST22b]. samples [SZM21]. sampling [GMR20, LLZ20a, SSLD20, YGT20, CKY20, GM20, LL20, LLZ20b]. Sard [SKN^{+}22]. Scalable [FDZ22, PRZ20]. Scalar [FN22]. Scalar-on-function [FN22]. scale [DFBL22, GM22a, MS21, SSYL20, Ber22, GM22b, LEZK^{+}22, SJS^{+}22]. scales [HNS21]. schemes [GLS21]. score [NSI20]. scores [RR23, Tan20]. search [GLS21, ZB22]. Searching [LSR^{+}22]. sectional [HDL20]. Seeded [KBLM23]. segmentation [KBLM23]. segmented [Che21]. selecting [TX22]. selection [CBM20, DFBL22, GLS21, KLY21, MZZ^{+}20, RY23, ST22a, SLCF20, SSYL20, SZM21, THT^{+}23, WPS22]. selective [Zha22b]. selector [HHLL23]. Semi [SKN^{+}22, ZB22]. Semi-exact [SKN^{+}22]. semi-supervised [ZB22]. Semiparametric [YPC20, DV21a, DV22, HDL20, Mao20, MSK^{+}20, PK22, SLCF20, SZW21, YCG20, ZL21a]. Sensitivity [CTGS22, HP21]. separability [ZOP22]. Separable [MSP23]. separation [BGN^{+}20, He21]. sequential [HZ22a, HZ22b, LWDL22]. series [DFW20, Zha21, Zha22a]. sets [SSR22]. shape [SCMH22]. shared [MLZ22]. shift [DFW20]. shrinkage [KF21, LDD20, SK22]. sided [COF20]. sign [MC22]. signals [WPS22]. signed [HP21, MB21]. Significance [MZ22]. simple [CNS23]. Simplified [Woo20]. simultaneous [CBM20]. size [SCMH22]. sketching [AAR21]. small [MO21, Sug20]. Smoothed [LLFT22]. smoothing [MZZ^{+}20, SZM21]. snippets [LWZ21]. Sobol [BDS22]. Sobol-MDA [BDS22]. solution [BDS22]. source [BGN^{+}20]. space [MLZ22, MZZ^{+}20, TX22, ZXZ22]. space-filling [MZZ^{+}20, TX22]. spaces [DRS23]. Sparse [PAJ22, YCG20, CBM20, JG21, LS23b, MO21, QLR23, WPS22, XL22]. Spatial [BGN^{+}20, DDB22, GPR^{+}23a]. specific [MSK^{+}20]. Specification [GT21, HNRC20]. specifications [ZD22]. spectra [CG22]. Spectral [GPR^{+}23a]. Spherical [FI23]. spline [SZM21]. splines [MZZ^{+}20]. Splitting [RY23]. squares [Azr23]. stage [CHCK23]. statistic [ZJB21]. Statistical [AAR21, SCMH22, DNC22, FK21, GT21, GR23, HMvB21, ZDS^{+}20]. statistics [WL22]. status [AVH21]. steps [CRRS21]. stochastic [FDS22, GD22, SSYL20]. strategies [BPBS21, RY23]. Stratification [LWDL22]. stratified [LY20]. structural [Ano23a, CMTT23, LRF21, SB23, YPC20, YLYG23]. structure [MLZ22, SWT20]. structured [MS22a]. structures [GT21, ZJB21]. studies [COF20, GR23, HZ22c, Ros20, RR23, ZZC21]. subdistribution [BKGF20]. subject [DV21a, DV22]. Subsampling [LS23b, WM21]. subset [HHLL23]. sufficient [LXYY22, YY22]. summary [WL22, ZDS^{+}20]. super [Che21]. super-efficiency [Che21]. superharmonicity [MS22b]. supervised [ZB22]. surrogate [WPTC20, YHF21]. survey [DS21]. survival [AVH21, CHCK23, DV21a, DV22, HNS21]. symmetric [LMP23]. systems [SZW21]. tail [Zha21, Zha22a]. tail-dependent [Zha21, Zha22a]. temporal [BDT23, SZW21]. test [Ber22, CLYZ20, GM22a, GM22b, HP21, LEZK^{+}22, LB21, Mao22, MC22, Ros20, SJS^{+}22, TZ22, WX22, WJ22, Wan23]. Testing [CCY22, CLC23, DS21, LZS20, YXZ23, AVCG20, BPBS21, COF20, Dob20, DRBW23, GR20, KM20, LKJR22, LLFT22, MZ22, WCL21]. tests [DK21, Dob20, GT21, HNRC20, MS22a, YZ23]. text [JLM21]. theorem [CNS23]. theory [LLLD23]. Thresholded [WA23]. tilted [YGT20]. time [CMTT23, DFW20, GLS21, GRR21, HNS21, KCB^{+}21, LS23a, QYK^{+}21a, QYK^{+}21b, SWD23, VF22, YPC20, ZL21b, Zha21, Zha22a, ZC21]. time-average [VF22]. time-varying [CMTT23, GRR21, KCB^{+}21, QYK^{+}21a, QYK^{+}21b, SWD23, ZL21b]. tolerance [VF20]. topological [BM21, Bub21, CO21, GGH^{+}21a, GGH^{+}21b]. training [CFS20]. transformations [MT21]. transition [HMZX21, Zha22a]. transport [GP22]. treat [Mao22]. treatment [BDT23, CHCK23, DV21b, LY20, LTM23, NS22, NW21, PK22, SWD23, WPTC20, WZRR21, YYS22]. treatments [CMTT23, Gun21]. tree [BPBS21, GMR20]. trend [PC22]. trials [YHF21]. truncation [BKGF20, HDL20]. two [HNS21, SK22, WX22, YZ23]. two-dimensional [SK22]. two-sample [WX22, YZ23]. type [TX22]. types [YCG20].

U [ZJB21]. U-statistic-based [ZJB21]. Unbiased [HJ20]. unequal [YGT20]. unified [Mao20]. Uniform [KKSC23, HP21]. unimodal [HMF22]. Uniqueness [ZS22]. unit [CCY22]. universal [DRBW23]. unknown [MS21, NBP20]. unmeasured [CTGS22, Ros20]. use [Hui21, VF20]. using [AVH21, COW22, DS21, LGR20, LXYY22, PGDM20].

vaccine [YHF21]. Valid [HZ22a, HZ22b]. validated [BUCFFH21]. validation [CKY20, FH20, GM20, LL20, LLZ20a, LLZ20b]. validity [Gun21]. value [AVCG20, CLZ22, ZS22]. values [VW20]. Variable [GPR23b, CBM20, CMTT23, GLS21, JD20, KM20, NKK21, ST22a, SZZ22, SLCF20, SSYL20, WZRR21]. variables [HHLL23, NS22, NBP20, SSR22, WA23, ZXZ22]. Variance [LW18, LZF20, LZW23, LW20]. variances [KZ23]. variant [MCFB22]. variate [FY21, YXZ23]. variational [FDZ22]. varying [CMTT23, GRR21, KCB^{+}21, QYK^{+}21a, QYK^{+}21b, SWD23, ZL21b]. vector [CLYZ20, MS21, ZC21]. vectors [BZ21]. versus [GR20]. very [GLS21]. via [BDS22, CRRS21, GP22, LD20, LZF20, LKJR22, MSP23, MCFB22, MZZ^{+}20, NSI20, VW20, ZYH22, ZZZ21, vdBRD21, vdBRD22]. visualization [Zha22a].

Wasserstein [BMS22]. Wavelet [CG22]. ways [Zha22b]. weighted [Azr23, MB21]. weights [CZ23, RC20, WZ20]. Whitney [Mao22]. Whittle [KP23]. wide [ZZC21]. Wilcoxon [Mao22]. Wilks [HMZX21]. windows [VF22]. Wishart [SK22]. without [Säv22].

Yor [LPR20].

zero [YLYG23]. zero-inflated [YLYG23].

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[CO21] Moo K. Chung and Hernando Ombao. Discussion of ‘event history and topological data analysis’. Biometrika, 108(4):775–778, December 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/108/4/775/6428641.

Cohen:2020:MOS

[COF20] P. L. Cohen, M. A. Olson, and C. B. Fogarty. Multivariate one-sided testing in matched observational studies as an adversarial game. Biometrika, 107(4):809–??, December 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/4/809/5850657.

Chandna:2022:LLG

[COW22] S. Chandna, S. C. Olhede, and P. J. Wolfe. Local linear graphon estimation using covariates. Biometrika, 109(3):721–734, September 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/109/3/721/6425670.

Clarte:2021:CAB

[CRRS21] Grégoire Clarté, Christian P. Robert, Robin J. Ryder, and Julien Stoehr. Componentwise approximate Bayesian computation via Gibbs-like steps. Biometrika, 108(3):591–607, September 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/108/3/591/5955756.

Ciocanea-Teodorescu:2022:SAU

[CTGS22] I. Ciocanea-Teodorescu, E. E. Gabriel, and A. Sjölander. Sensitivity analysis for unmeasured confounding in the estimation of marginal causal effects. Biometrika, 109(4):1101–1116, December 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/109/4/1101/6547041.

Czado:2023:DCB

[CV23] C. Czado and I. Van Keilegom. Dependent censoring based on parametric copulas. Biometrika, 110(3):721–738, September 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/110/3/721/6947986.

Chattopadhyay:2023:IWL

[CZ23] Ambarish Chattopadhyay and José R. Zubizarreta. On the implied weights of linear regression for causal inference. Biometrika, 110(3):615–629, September 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/110/3/615/6779968.

Cao:2020:MEB

[CZL20] Yuanpei Cao, Anru Zhang, and Hongzhe Li. Multisample estimation of bacterial composition matrices in metagenomics data. Biometrika, 107(1):75–??, March 2020. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/1/75/5663561.

Dey:2022:GGP

[DDB22] Debangan Dey, Abhirup Datta, and Sudipto Banerjee. Graphical Gaussian process models for highly multivariate spatial data. Biometrika, 109(4):993–1014, December 2022. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/109/4/993/
6449436.

Dimitriadis:2023:HCA

[DDH^{+}23] Timo Dimitriadis, Lutz Dümbgen, Alexander Henzi, Marius Puke, and Johanna Ziegel. Honest calibration assessment for binary outcome predictions. Biometrika, 110(3):663–680, September 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/110/3/663/6900929.

Demirkaya:2022:LSM

[DFBL22] Emre Demirkaya, Yang Feng, Pallavi Basu, and Jinchi Lv. Largescale model selection in misspecified generalized linear models. Biometrika, 109(1):123–136, March 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/1/123/6124351.

Dehling:2020:RMS

[DFW20] H. Dehling, R. Fried, and M. Wendler. A robust method for shift detection in time series. Biometrika, 107(3):647–??, September 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/3/647/5805447.

Diaz:2021:NEC

[DHRvDL21] I. Díaz, N. S. Hejazi, K. E. Rudolph, and M. J. van Der Laan. Nonparametric efficient causal mediation with intermediate confounders. Biometrika, 108(3):627–641, September 2021. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/108/3/627/
5924585.

Dunson:2020:HAF

[DJ20] D. B. Dunson and J. E. Johndrow. The Hastings algorithm at fifty. Biometrika, 107(1):1–??, March 2020. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/1/1/5686745.

Dette:2021:BET

[DK21] Holger Dette and Kevin Kokot. Bio-equivalence tests in functional data by maximum deviation. Biometrika, 108(4):895– 913, December 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/108/4/895/5958115.

Duan:2022:HAC

[DNC22] Rui Duan, Yang Ning, and Yong Chen. Heterogeneityaware and communication-efficient distributed statistical inference. Biometrika, 109(1):67–83, March 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/1/67/6134131.

Dobriban:2020:FCT

[Dob20] E. Dobriban. Fast closed testing for exchangeable local tests. Biometrika, 107(3):761–??, September 2020. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/3/761/5732870.

Dunn:2023:GUL

[DRBW23] Robin Dunn, Aaditya Ramdas, Sivaraman Balakrishnan, and Larry Wasserman. Gaussian universal likelihood ratio testing. Biometrika, 110(2):319–337, June 2023. CODEN BIOKAX.

ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/110/2/319/6835408.

Duanmu:2023:EMP

[DRS23] Haosui Duanmu, Daniel M Roy, and Aaron Smith. Existence of matching priors on compact spaces. Biometrika, 110(3):763– 776, September 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/110/3/763/6839928.

DaSilva:2021:TME

[DS21] D. N. Da Silva and C. J. Skinner. Testing for measurement error in survey data analysis using paradata. Biometrika, 108 (1):239–246, March 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/108/1/239/5880217.

Deresa:2021:SME

[DV21a] N. W. Deresa and I. Van Keilegom. On semiparametric modelling, estimation and inference for survival data subject to dependent censoring. Biometrika, 108(4):965–979, December 2021. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/108/4/965/

5958113. See correction [DV22].

Dukes:2021:ITE

[DV21b] Oliver Dukes and Stijn Vansteelandt. Inference for treatment effect parameters in potentially misspecified high-dimensional models. Biometrika, 108(2):321–334, June 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/108/2/321/5902826.

Deresa:2022:CSM

[DV22] N. W. Deresa and I. Van Keilegom. Correction to: ‘On semiparametric modelling, estimation and inference for survival data subject to dependent censoring’. Biometrika, 109(1):273, March 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/109/1/273/6355119. See [DV21a].

Duan:2020:BCR

[DYND20] Leo L. Duan, Alexander L. Young, Akihiko Nishimura, and David B. Dunson. Bayesian constraint relaxation. Biometrika, 107(1):191–??, March 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/107/1/191/5686747.

Escobar-Bach:2022:ECR

[EBMVZ22] Mikael Escobar-Bach, Ross Maller, Ingrid Van Keilegom, and Muzhi Zhao. Estimation of the cure rate for distributions in the Gumbel maximum domain of attraction under insufficient followup. Biometrika, 109(1):243–256, March 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/1/243/6070144.

Farewell:2022:MRS

[FDS22] D. M. Farewell, R. M. Daniel, and S. R. Seaman. Missing at random: a stochastic process perspective. Biometrika, 109 (1):227–241, March 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/109/1/227/6128501.

Fasano:2022:SAV

[FDZ22] Augusto Fasano, Daniele Durante, and Giacomo Zanella. Scalable and accurate variational Bayes for high-dimensional binary regression models. Biometrika, 109(4):901–919, December 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/109/4/901/6581071.

Fong:2020:MLC

[FH20] E. Fong and C. C. Holmes. On the marginal likelihood and cross-validation. Biometrika, 107(2):489–??, June 2020. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/2/489/5715611.

Fomichov:2023:SCD

[FI23] V. Fomichov and J. Ivanovs. Spherical clustering in detection of groups of concomitant extremes. Biometrika, 110(1):135–153, March 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/110/1/135/6551983.

Frongillo:2021:ECS

[FK21] Rafael M. Frongillo and Ian A. Kash. Elicitation complexity of statistical properties. Biometrika, 108(4):857–879, December 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/108/4/857/5955754.

Ferraty:2022:SFL

[FN22] F. Ferraty and S. Nagy. Scalar-on-function local linear regression and beyond. Biometrika, 109(2):439–455, June 2022. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/109/2/439/
6243862.

Fang:2021:MVL

[FY21] Junhan Fang and Grace Y. Yi. Matrix-variate logistic regression with measurement error. Biometrika, 108(1):83–97, March 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/108/1/83/5866971.

Gerber:2022:GSO

[GD22] M. Gerber and R. Douc. A global stochastic optimization particle filter algorithm. Biometrika, 109(4):937–955, December 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/109/4/937/6486527.

Garside:2021:EHT

[GGH^{+}21a] K. Garside, A. Gjoka, R. Henderson, H. Johnson, and I. Makarenko. Event history and topological data analysis. Biometrika, 108(4):757–773, December 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/108/4/757/5983325.

Garside:2021:REH

[GGH^{+}21b] K. Garside, A. Gjoka, R. Henderson, H. Johnson, and I. Makarenko. Rejoinder: ‘event history and topological data analysis’. Biometrika, 108(4):789–793, December 2021. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/108/4/789/
6409657.

Griffin:2021:SLM

[GLS21] J. E. Griffin, K. G. Latuszyński, and M. F. J. Steel. In search of lost mixing time: adaptive Markov chain Monte Carlo schemes for Bayesian variable selection with very large p. Biometrika, 108(1):53–69, March 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/108/1/53/5918057.

Gao:2020:DNC

[GM20] Chao Gao and Zongming Ma. Discussion of ‘Network crossvalidation by edge sampling’. Biometrika, 107(2):281–??, June 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/2/281/5837754. See [LLZ20a].

Gorsky:2022:MSF

[GM22a] S. Gorsky and L. Ma. Multi-scale Fisher’s independence test for multivariate dependence. Biometrika, 109(3):569–587, September 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/

article/109/3/569/6533498. See discussion [Ber22, LEZK^{+}22, SJS^{+}22] and rejoinder [GM22b].

Gorsky:2022:RMS

[GM22b] S. Gorsky and L. Ma. Rejoinder: ‘Multi-scale Fisher’s independence test for multivariate dependence’. Biometrika, 109(3): 605–609, September 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/109/3/605/6658429. See [GM22a, Ber22,

LEZK^{+}22, SJS^{+}22].

Green:2020:CTB

[GMR20] A. K. B. Green, T. H. McCormick, and A. E. Raftery. Consistency for the tree bootstrap in respondent-driven sampling. Biometrika, 107(2):497–??, June 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/107/2/497/5715616.

Ghodrati:2022:DDR

[GP22] Laya Ghodrati and Victor M. Panaretos. Distribution-on-distribution regression via optimal transport maps. Biometrika, 109(4):957–974, December 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/109/4/957/6515608.

Guan:2023:SAS

[GPR^{+}23a] Yawen Guan, Garritt L. Page, Brian J. Reich, Massimo Ventrucci, and Shu Yang. Spectral adjustment for spatial confounding. Biometrika, 110(3):699–719, September 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/110/3/699/6955604.

Guo:2023:VEG

[GPR23b] F Richard Guo, Emilija Perković, and Andrea Rotnitzky. Variable elimination, graph reduction and the efficient g-formula. Biometrika, 110(3):739–761, September 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/110/3/739/6833014.

Guo:2020:TMV

[GR20] F. Richard Guo and Thomas S. Richardson. On testing marginal versus conditional independence. Biometrika, 107(4):771–??, December 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/4/771/5875781.

Guo:2023:SRI

[GR23] Kevin Guo and Dominik Rothenhäusler. On the statistical role of inexact matching in observational studies. Biometrika, 110 (3):631–644, September 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/110/3/631/6854970.

Guo:2021:DET

[GRR21] F. Richard Guo, Thomas S. Richardson, and James M. Robins. Discussion of ‘Estimating time-varying causal excursion effects in mobile health with binary outcomes’. Biometrika, 108(3): 541–550, September 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/108/3/541/6350047. See [QYK^{+}21a].

Guo:2021:STC

[GT21] X. Guo and C. Y. Tang. Specification tests for covariance structures in high-dimensional statistical models. Biometrika, 108 (2):335–351, June 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/108/2/335/5903732.

Guan:2023:LCP

[Gua23] Leying Guan. Localized conformal prediction: a generalized inference framework for conformal prediction. Biometrika, 110 (1):33–50, March 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/110/1/33/6647831.

Guinness:2022:IMR

[Gui22] Joseph Guinness. Inverses of Matérn covariances on grids. Biometrika, 109(2):535–541, June 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/2/535/6168989.

Gunsilius:2021:NIV

[Gun21] F. F. Gunsilius. Nontestability of instrument validity under continuous treatments. Biometrika, 108(4):989–995, December 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/108/4/989/6035117.

Heuchenne:2020:ECS

[HDL20] C. Heuchenne, J. De Uña-Álvarez, and G. Laurent. Estimation from cross-sectional data under a semiparametric truncation model. Biometrika, 107(2):449–??, June 2020. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/2/449/5819203.

He:2021:LBD

[He21] Xu He. Lattice-based designs with quasi-optimal separation distance on all projections. Biometrika, 108(2):443–454, June 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/108/2/443/5866972.

Hu:2023:RBS

[HHLL23] Jianhua Hu, Jian Huang, Xiaoqian Liu, and Xu Liu. Response best-subset selector for multivariate regression with highdimensional response variables. Biometrika, 110(1):205–223, March 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/110/1/205/6633931.

Heng:2020:UHM

[HJ20] J. Heng and P. E. Jacob. ‘unbiased Hamiltonian Monte Carlo with couplings. Biometrika, 107(3):769–??, September 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/3/769/5875370.

Hu:2022:ADI

[HLW22] Yuchen Hu, Shuangning Li, and Stefan Wager. Average direct and indirect causal effects under interference. Biometrika, 109 (4):1165–1172, December 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/109/4/1165/6524620.

Heinrich-Mertsching:2022:MER

[HMF22] Claudio Heinrich-Mertsching and Tobias Fissler. Is the mode elicitable relative to unimodal distributions? Biometrika, 109 (4):1157–1164, December 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/109/4/1157/6491230.

Hazelton:2021:GAD

[HMvB21] M. L. Hazelton, M. R. Mcveagh, and B. van Brunt. Geometrically aware dynamic Markov bases for statistical linear inverse problems. Biometrika, 108(3):609–626, September 2021. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/108/3/609/
5918020.

He:2021:PTW

[HMZX21] Yinqiu He, Bo Meng, Zhenghao Zeng, and Gongjun Xu. On the phase transition of Wilks’ phenomenon. Biometrika, 108 (3):741–748, September 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/108/3/741/5911091.

Huang:2020:STC

[HNRC20] Jing Huang, Yang Ning, Nancy Reid, and Yong Chen. On specification tests for composite likelihood inference. Biometrika, 107 (4):907–??, December 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/107/4/907/5857277.

Hiabu:2021:NBE

[HNS21] M. Hiabu, J. P. Nielsen, and T. H. Scheike. Nonsmooth backfitting for the excess risk additive regression model with two survival time scales. Biometrika, 108(2):491–506, June 2021. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/108/2/491/
5869040.

Howard:2021:UGS

[HP21] S. R. Howard and S. D. Pimentel. The uniform general signed rank test and its design sensitivity. Biometrika, 108(2):381–396, June 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/108/2/381/5911093.

Hui:2021:UPQ

[Hui21] Francis K. C. Hui. On the use of a penalized quasilikelihood information criterion for generalized linear mixed models. Biometrika, 108(2):353–365, June 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/108/2/353/5899715.

Henzi:2022:CVS

[HZ22a] Alexander Henzi and Johanna F. Ziegel. Correction to: ‘valid sequential inference on probability forecast performance’. Biometrika, 109(4):1181–1182, December 2022. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article/
109/4/1181/6696629.

Henzi:2022:VSI

[HZ22b] Alexander Henzi and Johanna F. Ziegel. Valid sequential inference on probability forecast performance. Biometrika, 109 (3):647–663, September 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/109/3/647/6375942.

Huang:2022:FHF

[HZ22c] C. Huang and H. Zhu. Functional hybrid factor regression model for handling heterogeneity in imaging studies. Biometrika, 109 (4):1133–1148, December 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/109/4/1133/6519305.

Jin:2020:NAA

[JA20] Shaobo Jin and Björn Andersson. A note on the accuracy of adaptive Gauss–Hermite quadrature. Biometrika, 107(3): 737–??, September 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/107/3/737/5732875.

Jiang:2020:MEB

[JD20] Zhichao Jiang and Peng Ding. Measurement errors in the binary instrumental variable model. Biometrika, 107(1):238–??, March 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/1/238/5637447.

Jeong:2021:PCS

[JG21] Seonghyun Jeong and Subhashis Ghosal. Posterior contraction in sparse generalized linear models. Biometrika, 108(2):367–379, June 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/108/2/367/5905471.

Jentsch:2021:PRR

[JLM21] Carsten Jentsch, Eun Ryung Lee, and Enno Mammen. Poisson reduced-rank models with an application to political text data. Biometrika, 108(2):455–468, June 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/108/2/455/5879273.

Kovacs:2023:SBS

[KBLM23] S. Kovács, P. Bühlmann, H. Li, and A. Munk. Seeded binary segmentation: a general methodology for fast and optimal changepoint detection. Biometrika, 110(1):249–256, March 2023. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/110/1/249/
6747166.

Kuchibhotla:2023:MRH

[KBW23] Arun Kumar Kuchibhotla, Sivaraman Balakrishnan, and Larry Wasserman. Median regularity and honest inference. Biometrika, 110(3):831–838, September 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/110/3/831/6989628.

Kim:2021:DET

[KCB^{+}21] S. Kim, H. Cho, D. Bang, D. De Marchi, H. El-Zaatari, K. S. Shah, M. Valancius, T. M. Zikry, and M. R. Kosorok. Discussion of ‘Estimating time-varying causal excursion effects in mobile health with binary outcomes’. Biometrika, 108(3):529– 533, September 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/108/3/529/6350038. See [QYK^{+}21a].

Kosmidis:2021:JPP

[KF21] Ioannis Kosmidis and David Firth. Jeffreys-prior penalty, finiteness and shrinkage in binomial-response generalized linear models. Biometrika, 108(1):71–82, March 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/108/1/71/5880219.

Klaassen:2023:UIH

[KKSC23] S. Klaassen, J. Kueck, M. Spindler, and V. Chernozhukov. Uniform inference in high-dimensional Gaussian graphical models. Biometrika, 110(1):51–68, March 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/110/1/51/6595019.

Kuffner:2021:BBO

[KLY21] T. A. Kuffner, S. M. S. Lee, and G. A. Young. Block bootstrap optimality and empirical block selection for sample quantiles with dependent data. Biometrika, 108(3):675–692, September 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/108/3/675/5905470.

Kedagni:2020:GII

[KM20] Désiré Kédagni and Ismael Mourifié. Generalized instrumental inequalities: testing the instrumental variable independence assumption. Biometrika, 107(3):661–??, September 2020. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/3/661/5767137.

Kong:2020:RPB

[Kon20] Xinbing Kong. A random-perturbation-based rank estimator of the number of factors. Biometrika, 107(2):505–??, June 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/2/505/5721277.

Kreiss:2023:BWE

[KP23] J.-P Kreiss and E. Paparoditis. Bootstrapping Whittle estimators. Biometrika, 110(2):499–518, June 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/110/2/499/6659094.

Kong:2022:ICE

[KYW22] Dehan Kong, Shu Yang, and Linbo Wang. Identifiability of causal effects with multiple causes and a binary outcome. Biometrika, 109(1):265–272, March 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/109/1/265/6168988.

Kwon:2023:MBE

[KZ23] Yeil Kwon and Zhigen Zhao. On F -modelling-based empirical Bayes estimation of variances. Biometrika, 110(1):69–81, March 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/110/1/69/6548155.

Lei:2021:AFE

[LB21] Lihua Lei and Peter J. Bickel. An assumption-free exact test for fixed-design linear models with exchangeable errors. Biometrika, 108(2):397–412, June 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/108/2/397/5913387.

Lei:2020:CCD

[LCL20] Jing Lei, Kehui Chen, and Brian Lynch. Consistent community detection in multi-layer network data. Biometrika, 107 (1):61–??, March 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/107/1/61/5684881.

Li:2020:CLM

[LD20] Didong Li and David B. Dunson. Classification via local manifold approximation. Biometrika, 107(4):1013–??, December 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/4/1013/5871505.

Lei:2021:RAC

[LD21] Lihua Lei and Peng Ding. Regression adjustment in completely randomized experiments with a diverging number of covariates. Biometrika, 108(4):815–828, December 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/108/4/815/6042141.

Legramanti:2020:BCS

[LDD20] Sirio Legramanti, Daniele Durante, and David B. Dunson. Bayesian cumulative shrinkage for infinite factorizations. Biometrika, 107(3):745–??, September 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:

//academic.oup.com/biomet/article-abstract/107/3/745/
5847840.

Lee:2022:DMS

[LEZK^{+}22] D. Lee, H. El-Zaatari, M. R. Kosorok, X. Li, and K. Zhang. Discussion of ‘Multi-scale Fisher’s independence test for multivariate dependence’. Biometrika, 109(3):593–596, September 2022. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/109/3/593/

6674588. See [GM22a, Ber22, SJS^{+}22, GM22b].

Li:2020:DCM

[LGL20] Wei Li, Yuwen Gu, and Lan Liu. Demystifying a class of multiply robust estimators. Biometrika, 107(4):919–??, December 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/4/919/5843892.

Lu:2023:ECE

[LGL^{+}23] Zitong Lu, Zhi Geng, Wei Li, Shengyu Zhu, and Jinzhu Jia. Evaluating causes of effects by posterior effects of causes. Biometrika, 110(2):449–465, June 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/110/2/449/6637513.

Lee:2020:AGD

[LGR20] Jarod Y. L. Lee, Peter J. Green, and Louise M. Ryan. Analysis of grouped data using conjugate generalized linear mixed models. Biometrika, 107(1):231–??, March 2020. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/1/231/5607066.

Lin:2023:BPC

[LH23] Z. Lin and F. Han. On boosting the power of Chatterjee’s rank correlation. Biometrika, 110(2):283–299, June 2023. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/110/2/283/
6670792.

Liu:2022:FPC

[LKJR22] Molei Liu, Eugene Katsevich, Lucas Janson, and Aaditya Ramdas. Fast and powerful conditional randomization testing via distillation. Biometrika, 109(2):277–293, June 2022. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/109/2/277/
6317827.

Lei:2020:DNC

[LL20] J. Lei and K. Z. Lin. Discussion of ‘Network cross-validation by edge sampling’. Biometrika, 107(2):285–??, June 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/2/285/5837741. See [LLZ20a].

Luo:2021:ODP

[LL21] Wei Luo and Bing Li. On order determination by predictor augmentation. Biometrika, 108(3):557–574, September 2021. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/108/3/557/
5917626.

Loper:2022:SNT

[LLFT22] J. H. Loper, L. Lei, W. Fithian, and W. Tansey. Smoothed nested testing on directed acyclic graphs. Biometrika, 109(2):457–471, June 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/109/2/457/6362862.

Lu:2023:DBT

[LLLD23] Xin Lu, Tianle Liu, Hanzhong Liu, and Peng Ding. Design-based theory for cluster rerandomization. Biometrika, 110(2):467–483, June 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/110/2/467/6655724.

Li:2021:MCM

[LLT21] Wenlong Li, Min-Qian Liu, and Boxin Tang. A method of constructing maximin distance designs. Biometrika, 108(4):845– 855, December 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/108/4/845/5942967.

Li:2020:NCV

[LLZ20a] Tianxi Li, Elizaveta Levina, and Ji Zhu. Network cross-validation by edge sampling. Biometrika, 107(2):257–??, June 2020. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/2/257/5816043. See discussion [CKY20, GM20,

LL20] and rejoinder [LLZ20b].

Li:2020:RNC

[LLZ20b] Tianxi Li, Elizaveta Levina, and Ji Zhu. Rejoinder: ‘Network cross-validation by edge sampling’. Biometrika, 107(2):289–??, June 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/2/289/5837737. See [LLZ20a].

Lin:2023:AMS

[LMP23] Z Lin, H G Müller, and B U Park. Additive models for symmetric positive-definite matrices and Lie groups. Biometrika, 110 (2):361–379, June 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/110/2/361/6730723.

Li:2020:EH

[LMSW20] Housen Li, Axel Munk, Hannes Sieling, and Guenther Walther. The essential histogram. Biometrika, 107(2):347–??, June 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/2/347/5733266.

Lijoi:2020:PYM

[LPR20] Antonio Lijoi, Igor Prünster, and Tommaso Rigon. The Pitman– Yor multinomial process for mixture modelling. Biometrika, 107 (4):891–??, December 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/107/4/891/5854095.

Lei:2021:GIF

[LRF21] Lihua Lei, Aaditya Ramdas, and William Fithian. A general interactive framework for false discovery rate control under structural constraints. Biometrika, 108(2):253–267, June 2021. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/108/2/253/
5879274.

Ludkin:2023:HHD

[LS23a] M. Ludkin and C. Sherlock. Hug and hop: a discrete-time, nonreversible Markov chain Monte Carlo algorithm. Biometrika, 110 (2):301–318, June 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/110/2/301/6633932.

Lunde:2023:SSG

[LS23b] Robert Lunde and Purnamrita Sarkar. Subsampling sparse graphons under minimal assumptions. Biometrika, 110(1):15–32, March 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/110/1/15/6598813.

Li:2022:SRA

[LSR^{+}22] S. Li, M. Sesia, Y. Romano, E. Candès, and C. Sabatti. Searching for robust associations with a multi-environment knockoff filter. Biometrika, 109(3):611–629, September 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/3/611/6415825.

Liu:2023:LAT

[LTM23] Hanzhong Liu, Fuyi Tu, and Wei Ma. Lasso-adjusted treatment effect estimation under covariate-adaptive randomization. Biometrika, 110(2):431–447, June 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/110/2/431/6609758.

Lee:2018:VEP

[LW18] A. Lee and N. Whiteley. Variance estimation in the particle filter. Biometrika, 105(3):609–625, September 1, 2018.

CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/105/3/609/5045658. See correction [LW20].

Lee:2020:CVE

[LW20] A. Lee and N. Whiteley. Correction: ‘Variance estimation in the particle filter’. Biometrika, 107(1):255–??, March 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/1/255/5717456. See [LW18].

Li:2022:SOR

[LWDL22] Yichao Li, Wenshuo Wang, K. E. Deng, and Jun S. Liu. Stratification and optimal resampling for sequential Monte Carlo. Biometrika, 109(1):181–194, March 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/1/181/6132360.

Lin:2021:BEF

[LWZ21] Zhenhua Lin, Jane-Ling Wang, and Qixian Zhong. Basis expansions for functional snippets. Biometrika, 108(3):709– 726, September 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/108/3/709/5937818.

Luo:2022:IMM

[LXYY22] Wei Luo, Lingzhou Xue, Jiawei Yao, and Xiufan Yu. Inverse moment methods for sufficient forecasting using high-dimensional predictors. Biometrika, 109(2):473–487, June 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/109/2/473/
6309457.

Liu:2020:RAA

[LY20] Hanzhong Liu and Yuehan Yang. Regression-adjusted average treatment effect estimates in stratified randomized experiments. Biometrika, 107(4):935–??, December 2020. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/4/935/5857286.

Lin:2021:FRM

[LY21] Zhenhua Lin and Fang Yao. Functional regression on the manifold with contamination. Biometrika, 108(1):167–181, March 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/108/1/167/5874121.

Liu:2020:EEV

[LZF20] X. Liu, S. Zheng, and X. Feng. Estimation of error variance via ridge regression. Biometrika, 107(2):481–??, June 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/2/481/5716270.

Lee:2020:TCM

[LZS20] C. E. Lee, X. Zhang, and X. Shao. Testing conditional mean independence for functional data. Biometrika, 107(2):331–??, June 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/2/331/5716269.

Lou:2023:HDA

[LZW23] Zhipeng Lou, Xianyang Zhang, and Wei Biao Wu. Highdimensional analysis of variance in multivariate linear regression. Biometrika, 110(3):777–797, September 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/110/3/777/6991165.

Mao:2020:UAC

[Mao20] Lu Mao. A unified approach to the calculation of information operators in semiparametric models. Biometrika, 107(4): 983–??, December 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/107/4/983/5857283.

Mao:2022:REI

[Mao22] Lu Mao. On the relative efficiency of the intent-to-treat Wilcoxon–Mann–Whitney test in the presence of noncompliance. Biometrika, 109(3):873–880, September 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/3/873/6409853.

Ma:2021:ADM

[MB21] Rong Ma and Ian Barnett. The asymptotic distribution of modularity in weighted signed networks. Biometrika, 108(1):1–16, March 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/108/1/1/5869041.

Moon:2022:IRS

[MC22] Haeun Moon and Kehui Chen. Interpoint-ranking sign covariance for the test of independence. Biometrika, 109(1):165–179, March 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/109/1/165/6137831.

Masoero:2022:MLP

[MCFB22] Lorenzo Masoero, Federico Camerlenghi, Stefano Favaro, and Tamara Broderick. More for less: predicting and maximizing genomic variant discovery via Bayesian nonparametrics. Biometrika, 109(1):17–32, March 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/1/17/6146908.

Ma:2021:OEB

[MCL21] Rong Ma, T. Tony Cai, and Hongzhe Li. Optimal estimation of bacterial growth rates based on a permuted monotone matrix. Biometrika, 108(3):693–708, September 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/108/3/693/5919580.

Marrs:2023:RER

[MFM23] F. W. Marrs, B. K. Fosdick, and T. H. Mccormick. Regression of exchangeable relational arrays. Biometrika, 110(1):265–272, March 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/110/1/265/6591197.

MacDonald:2022:LSM

[MLZ22] P. W. MacDonald, E. Levina, and J. Zhu. Latent space models for multiplex networks with shared structure. Biometrika, 109 (3):683–706, September 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/109/3/683/6425671.

Matsushita:2021:JEL

[MO21] Yukitoshi Matsushita and Taisuke Otsu. Jackknife empirical likelihood: small bandwidth, sparse network and high-dimensional asymptotics. Biometrika, 108(3):661–674, September 2021. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/108/3/661/
5918019.

Ma:2021:HIR

[MPHF21] Huijuan Ma, Limin Peng, Chiung-Yu Huang, and Haoda Fu. Heterogeneous individual risk modelling of recurrent events. Biometrika, 108(1):183–198, March 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/108/1/183/5934915.

Maruyama:2021:AEM

[MS21] Y. Maruyama and W. E. Strawderman. Admissible estimators of a multivariate normal mean vector when the scale is unknown. Biometrika, 108(4):997–1003, December 2021. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/108/4/997/
6040734.

Mammen:2022:BTG

[MS22a] E. Mammen and S. Sperlich. Backfitting tests in generalized structured models. Biometrika, 109(1):137–152, March 2022. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/109/1/137/
6119342.

Matsuda:2022:EUM

[MS22b] T. Matsuda and W. E. Strawderman. Estimation under matrix quadratic loss and matrix superharmonicity. Biometrika, 109(2):503–519, June 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/109/2/503/6239704.

Miles:2020:SEP

[MSK^{+}20] C. H. Miles, I. Shpitser, P. Kanki, S. Meloni, and E. J. Tchetgen Tchetgen. On semiparametric estimation of a path-specific effect in the presence of mediator-outcome confounding. Biometrika, 107(1):159–??, March 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/107/1/159/5638939.

Masak:2023:SEC

[MSP23] T. Masak, S. Sarkar, and V. M. Panaretos. Separable expansions for covariance estimation via the partial inner product. Biometrika, 110(1):225–247, March 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/110/1/225/6609757.

McCullagh:2021:LAQ

[MT21] P. McCullagh and M. F. Tresoldi. A likelihood analysis of quantile-matching transformations. Biometrika, 108(1):247–251, March 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/108/1/247/5878256.

Mukherjee:2020:BME

[Muk20] K. Mukherjee. Bootstrapping m-estimators in generalized autoregressive conditional heteroscedastic models. Biometrika, 107 (3):753–??, September 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/107/3/753/5831314.

Mukhopadhyay:2020:NAH

[MW20] Subhadeep Mukhopadhyay and Kaijun Wang. A nonparametric approach to high-dimensional k-sample comparison problems. Biometrika, 107(3):555–??, September 2020. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/3/555/5856303.

McKeague:2022:STC

[MZ22] Ian W. McKeague and Xin Zhang. Significance testing for canonical correlation analysis in high dimensions. Biometrika, 109(4): 1067–1083, December 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/109/4/1067/6430972.

Meng:2020:MEA

[MZZ^{+}20] Cheng Meng, Xinlian Zhang, Jingyi Zhang, Wenxuan Zhong, and Ping Ma. More efficient approximation of smoothing splines via space-filling basis selection. Biometrika, 107(3):723–??, September 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/3/723/5831923.

Nghiem:2020:ELE

[NBP20] Linh H. Nghiem, Michael C. Byrd, and Cornelis J. Potgieter. Estimation in linear errors-in-variables models with unknown error distribution. Biometrika, 107(4):841–??, December 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/4/841/5841614.

Nishimura:2020:DHM

[NDL20] Akihiko Nishimura, David B. Dunson, and Jianfeng Lu. Discontinuous Hamiltonian Monte Carlo for discrete parameters and discontinuous likelihoods. Biometrika, 107(2):365–??, June 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/2/365/5799014.

Na:2021:EDL

[NKK21] S. Na, M. Kolar, and O. Koyejo. Estimating differential latent variable graphical models with applications to brain connectivity. Biometrika, 108(2):425–442, June 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/108/2/425/5901536.

Newey:2022:HCC

[NS22] W. K. Newey and S. Stouli. Heterogeneous coefficients, control variables and identification of multiple treatment effects. Biometrika, 109(3):865–872, September 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/3/865/6446028.

Ning:2020:REC

[NSI20] Yang Ning, Peng Sida, and Kosuke Imai. Robust estimation of causal effects via a high-dimensional covariate balancing propensity score. Biometrika, 107(3):533–??, September 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/3/533/5850656.

Nie:2021:QOE

[NW21] X. Nie and S. Wager. Quasi-oracle estimation of heterogeneous treatment effects. Biometrika, 108(2):299–319, June 2021. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/108/2/299/
5911092.

Park:2022:SFL

[PAJ22] Juhyun Park, Jeongyoun Ahn, and Yongho Jeon. Sparse functional linear discriminant analysis. Biometrika, 109(1):209–226, March 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/109/1/209/6064132.

Padilla:2022:RBQ

[PC22] Oscar Hernan Madrid Padilla and Sabyasachi Chatterjee. Risk bounds for quantile trend filtering. Biometrika, 109(3):751– 768, September 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/109/3/751/6371864.

Plumlee:2021:CGD

[PEAL21] M. Plumlee, C. B. Erickson, B. E. Ankenman, and E. Lawrence. Composite grid designs for adaptive computer experiments with fast inference. Biometrika, 108(3):749–755, September 2021. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/108/3/749/
5923289.

Payne:2020:CDE

[PGDM20] R. D. Payne, N. Guha, Y. Ding, and B. K. Mallick. A conditional density estimation partition model using logistic Gaussian processes. Biometrika, 107(1):173–??, March 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/1/173/5658674.

Park:2022:ESE

[PK22] C. Park and H. Kang. Efficient semiparametric estimation of network treatment effects under partial interference. Biometrika, 109 (4):1015–1031, December 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/109/4/1015/6524621.

Papaspiliopoulos:2020:SIC

[PRZ20] O. Papaspiliopoulos, G. O. Roberts, and G. Zanella. Scalable inference for crossed random effects models. Biometrika, 107 (1):25–??, March 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/107/1/25/5626077.

Padilla:2020:ANR

[PSCW20] Oscar Hernan Madrid Padilla, James Sharpnack, Yanzhen Chen, and Daniela M. Witten. Adaptive nonparametric regression with the K-nearest neighbour fused lasso. Biometrika, 107(2):293–??, June 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/2/293/5717457.

Qiu:2023:GBS

[QLR23] Yixuan Qiu, Jing Lei, and Kathryn Roeder. Gradient-based sparse principal component analysis with extensions to online learning. Biometrika, 110(2):339–360, June 2023. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/110/2/339/
6640166.

Qiao:2020:DFG

[QQJG20] Xinghao Qiao, Cheng Qian, Gareth M. James, and Shaojun Guo. Doubly functional graphical models in high dimensions. Biometrika, 107(2):415–??, June 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:

//academic.oup.com/biomet/article-abstract/107/2/415/
5733267.

Qian:2021:ETV

[QYK^{+}21a] Tianchen Qian, Hyesun Yoo, Predrag Klasnja, Daniel Almirall, and Susan A. Murphy. Estimating time-varying causal excursion effects in mobile health with binary outcomes. Biometrika, 108 (3):507–527, September 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/108/3/507/5901535. See discussion

[KCB^{+}21, ZL21b, GRR21] and rejoinder [QYK^{+}21b]..

Qian:2021:RET

[QYK^{+}21b] Tianchen Qian, Hyesun Yoo, Predrag Klasnja, Daniel Almirall, and Susan A. Murphy. Rejoinder: ‘Estimating time-varying causal excursion effects in mobile health with binary outcomes’. Biometrika, 108(3):551–555, September 2021. CODEN BIOKAX.

ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/108/3/551/6350029. See

[QYK^{+}21a].

Roverato:2020:PWC

[RC20] Alberto Roverato and Robert Castelo. Path weights in concentration graphs. Biometrika, 107(3):705–??, September 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/3/705/5823573.

Rigon:2023:GBF

[RHD23] Tommaso Rigon, Amy H Herring, and David B Dunson. A generalized Bayes framework for probabilistic clustering. Biometrika, 110(3):559–578, September 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/110/3/559/6992658.

Rosenbaum:2020:CTD

[Ros20] P. R. Rosenbaum. A conditional test with demonstrated insensitivity to unmeasured bias in matched observational studies. Biometrika, 107(4):827–??, December 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:

//academic.oup.com/biomet/article-abstract/107/4/827/
5857271.

Rosenbaum:2023:PSD

[RR23] P. R. Rosenbaum and D. B. Rubin. Propensity scores in the design of observational studies for causal effects. Biometrika, 110(1):1–13, March 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/110/1/1/6726181.

Rotnitzky:2021:CPM

[RSR21] A. Rotnitzky, E. Smucler, and J. M. Robins. Characterization of parameters with a mixed bias property. Biometrika, 108(1):231–238, March 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/108/1/231/5899828.

Rasines:2023:SSP

[RY23] D. García Rasines and G. A. Young. Splitting strategies for post-selection inference. Biometrika, 110(3):597–614, September 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/110/3/597/6955603.

Savje:2022:IMR

[Säv22] F. Sävje. On the inconsistency of matching without replacement. Biometrika, 109(2):551–558, June 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/2/551/6308304.

Schultheiss:2023:ARL

[SB23] C. Schultheiss and P. Bühlmann. Ancestor regression in linear structural equation models. Biometrika, ??(??), March 2023. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL https://doi.org/10.1093/biomet/asad008. See correc-

tion [Ano23a].

Song:2022:ADF

[SC22] Hoseung Song and Hao Chen. Asymptotic distribution-free changepoint detection for data with repeated observations. Biometrika, 109(3):783–798, September 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/3/783/6377777.

Schiavon:2022:GIF

[SCD22] L. Schiavon, A. Canale, and D. B. Dunson. Generalized infinite factorization models. Biometrika, 109(3):817–835, September 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/109/3/817/6422529.

Shen:2023:LMR

[SCHL23] Guohao Shen, Kani Chen, Jian Huang, and Yuanyuan Lin. Linearized maximum rank correlation estimation. Biometrika, 110 (1):187–203, March 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/110/1/187/6581069.

Sun:2022:SIS

[SCMH22] Yifei Sun, Sy Han Chiou, Kieren A. Marr, and Chiung-Yu Huang. Statistical inference on shape and size indexes for counting processes. Biometrika, 109(1):195–208, March 2022. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/109/1/195/
6134132.

Schmon:2021:LSA

[SDDP21] S. M. Schmon, G. Deligiannidis, A. Doucet, and M. K. Pitt. Large-sample asymptotics of the pseudo-marginal method. Biometrika, 108(1):37–51, March 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/108/1/37/5869975.

Shi:2022:PCR

[SDH22] H. Shi, M. Drton, and F. Han. On the power of Chatterjee’s rank correlation. Biometrika, 109(2):317–333, June 2022. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/109/2/317/
6259083.

Sen:2022:PFE

[Sen22] Deborshee Sen. Particle filter efficiency under limited communication. Biometrika, 109(4):921–935, December 2022. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/109/4/921/
6535704.

Schrab:2022:DMS

[SJS^{+}22] A. Schrab, W. Jitkrittum, Z. Szabó, D. Sejdinovic, and A. Gretton. Discussion of ‘Multi-scale Fisher’s independence test for multivariate dependence’. Biometrika, 109(3):597–603, September 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/109/3/597/6674575. See [GM22a, Ber22, LEZK^{+}22,

GM22b].

Sei:2022:CSP

[SK22] T. Sei and F. Komaki. A correlation-shrinkage prior for Bayesian prediction of the two-dimensional Wishart model. Biometrika, 109(4):1173–1180, December 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/4/1173/6519299.

South:2022:SEC

[SKN^{+}22] L. F. South, T. Karvonen, C. Nemeth, M. Girolami, and C. J. Oates. Semi-exact control functionals from Sard’s method.

Biometrika, 109(2):351–367, June 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/2/351/6309456.

Shin:2020:EEV

[SLCF20] Sunyoung Shin, Yufeng Liu, Stephen R. Cole, and Jason P. Fine. Ensemble estimation and variable selection with semiparametric regression models. Biometrika, 107(2):433–??, June 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/2/433/5820551.

Sen:2020:EPS

[SSLD20] Deborshee Sen, Matthias Sachs, Jianfeng Lu, and David B. Dunson. Efficient posterior sampling for high-dimensional imbalanced logistic regression. Biometrika, 107(4):1005–??, December 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/4/1005/5858314.

Smucler:2022:EAS

[SSR22] E. Smucler, F. Sapienza, and A. Rotnitzky. Efficient adjustment sets in causal graphical models with hidden variables. Biometrika, 109(1):49–65, March 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/109/1/49/6174686.

Song:2020:ESG

[SSYL20] Qifan Song, Yan Sun, Mao Ye, and Faming Liang. Extended stochastic gradient Markov chain Monte Carlo for large-scale Bayesian variable selection. Biometrika, 107(4):997–??, December 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/4/997/5871037.

Sarkar:2022:ABH

[ST22a] Sanat K. Sarkar and Cheng Yong Tang. Adjusting the Benjamini– Hochberg method for controlling the false discovery rate in knockoff-assisted variable selection. Biometrika, 109(4):1149– 1155, December 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/109/4/1149/6491231.

Sherlock:2022:DBP

[ST22b] C. Sherlock and A. H. Thiery. A discrete bouncy particle sampler. Biometrika, 109(2):335–349, June 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/2/335/6151695.

Sugasawa:2020:REB

[Sug20] S Sugasawa. Robust empirical Bayes small area estimation with density power divergence. Biometrika, 107(2):467–??, June 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/2/467/5717453.

Shi:2023:ATV

[SWD23] J Shi, Z Wu, and W Dempsey. Assessing time-varying causal effect moderation in the presence of cluster-level treatment effect heterogeneity and interference. Biometrika, 110(3):645– 662, September 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/110/3/645/6845450.

Simpson:2020:DDS

[SWT20] E. S. Simpson, J. L. Wadsworth, and J. A. Tawn. Determining the dependence structure of multivariate extremes. Biometrika, 107(3):513–??, September 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/107/3/513/5831922.

Solus:2021:CGG

[SWU21] L. Solus, Y. Wang, and C. Uhler. Consistency guarantees for greedy permutation-based causal inference algorithms. Biometrika, 108(4):795–814, December 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/108/4/795/6062392.

Sit:2021:EHA

[SYY21] T. Sit, Z. Ying, and Y. Yu. Event history analysis of dynamic networks. Biometrika, 108(1):223–230, March 2021. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/108/1/223/
5910796.

Sun:2021:AES

[SZM21] Xiaoxiao Sun, Wenxuan Zhong, and Ping Ma. An asymptotic and empirical smoothing parameters selection method for smoothing spline ANOVA models in large samples. Biometrika, 108 (1):149–166, March 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/108/1/149/5897688.

Sun:2021:MTB

[SZW21] Ming Sun, Donglin Zeng, and Yuanjia Wang. Modelling temporal biomarkers with semiparametric nonlinear dynamical systems. Biometrika, 108(1):199–214, March 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/108/1/199/5910800.

Shi:2022:HDL

[SZZ22] Pixu Shi, Yuchen Zhou, and Anru R. Zhang. High-dimensional log-error-in-variable regression with applications to microbial compositional data analysis. Biometrika, 109(2):405–420, June 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/109/2/405/6203806.

Tan:2020:RCE

[Tan20] Z. Tan. Regularized calibrated estimation of propensity scores with model misspecification and high-dimensional data. Biometrika, 107(1):137–??, March 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http:

//academic.oup.com/biomet/article-abstract/107/1/137/
5658668.

Taylor:2023:DIE

[TCH23] Jeremy M. G. Taylor, Kyuseong Choi, and Peisong Han. Data integration: exploiting ratios of parameter estimates from a reduced external model. Biometrika, 110(1):119–134, March 2023. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/110/1/119/
6567343.

Tudball:2023:SCP

[THT^{+}23] Matthew J Tudball, Rachael A Hughes, Kate Tilling, Jack Bowden, and Qingyuan Zhao. Sample-constrained partial identification with application to selection bias. Biometrika, 110 (2):485–498, June 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/110/2/485/6649721.

Tian:2022:MAT

[TX22] Ye Tian and Hongquan Xu. A minimum aberration-type criterion for selecting space-filling designs. Biometrika, 109(2):489–501, June 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/109/2/489/6203807.

Tyler:2020:LE

[TY20] David E. Tyler and Mengxi Yi. Lassoing eigenvalues. Biometrika, 107(2):397–??, June 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article-abstract/107/2/397/5733265.

Tan:2022:ICM

[TZ22] Falong Tan and Lixing Zhu. Integrated conditional moment test and beyond: when the number of covariates is divergent. Biometrika, 109(1):103–122, March 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/1/103/6137833.

vandenBoom:2021:APH

[vdBRD21] W. van den Boom, G. Reeves, and D. B. Dunson. Approximating posteriors with high-dimensional nuisance parameters via integrated rotated Gaussian approximation. Biometrika, 108(2):269–282, June 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/108/2/269/5897408. See correction

[vdBRD22].

vandenBoom:2022:CAP

[vdBRD22] W. van den Boom, G. Reeves, and D. B. Dunson. Correction to: ‘Approximating posteriors with high-dimensional nuisance parameters via integrated rotated Gaussian approximation’. Biometrika, 109(1):275, March 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/1/275/6373000. See

[vdBRD21].

Vihola:2020:UAB

[VF20] Matti Vihola and Jordan Franks. On the use of approximate Bayesian computation Markov chain Monte Carlo with inflated tolerance and post-correction. Biometrika, 107(2):381–??, June 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/2/381/5721278.

Vats:2022:LLW

[VF22] D. Vats and J. M. Flegal. Lugsail lag windows for estimating time-average covariance matrices. Biometrika, 109(3):735– 750, September 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/109/3/735/6395353.

Vats:2022:EBF

[VGLR22] D. Vats, F. B. Gonçalves, K. Latuszy’nski, and G. O. Roberts. Efficient Bernoulli factory Markov chain Monte Carlo for intractable posteriors. Biometrika, 109(2):369–385, June 2022. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/109/2/369/
6296586.

Vogrinc:2023:ODB

[VLZ23] Jure Vogrinc, Samuel Livingstone, and Giacomo Zanella. Optimal design of the Barker proposal and other locally balanced Metropolis–Hastings algorithms. Biometrika, 110(3):579– 595, September 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/110/3/579/6764577.

Vovk:2020:CVA

[VW20] Vladimir Vovk and Ruodu Wang. Combining p-values via averaging. Biometrika, 107(4):791–??, December 2020. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/4/791/5856302.

Wang:2023:TGL

[WA23] Minjie Wang and Genevera I. Allen. Thresholded graphical lasso adjusts for latent variables. Biometrika, 110(3):681–697, September 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/110/3/681/6820916.

Wang:2023:RDA

[Wan23] Shulei Wang. Robust differential abundance test in compositional data. Biometrika, 110(1):169–185, March 2023. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/110/1/169/
6590648.

Wang:2021:HTP

[WCL21] Shulei Wang, T. Tony Cai, and Hongzhe Li. Hypothesis testing for phylogenetic composition: a minimum-cost flow perspective. Biometrika, 108(1):17–36, March 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/108/1/17/5870283.

Wang:2020:HDC

[WD20] Y. Samuel Wang and Mathias Drton. High-dimensional causal discovery under non-Gaussianity. Biometrika, 107(1):41–??, March 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/1/41/5607065.

Wang:2022:HDP

[WJ22] Wenshuo Wang and Lucas Janson. A high-dimensional power analysis of the conditional randomization test and knockoffs. Biometrika, 109(3):631–645, September 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/3/631/6415822.

Wang:2022:EGC

[WL22] Jianqiao Wang and Hongzhe Li. Estimation of genetic correlation with summary association statistics. Biometrika, 109 (2):421–438, June 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/109/2/421/6273186.

Wang:2021:OSQ

[WM21] Haiying Wang and Yanyuan Ma. Optimal subsampling for quantile regression in big data. Biometrika, 108(1):99–112, March 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/108/1/99/5874120.

Wood:2020:SIN

[Woo20] Simon N. Wood. Simplified integrated nested Laplace approximation. Biometrika, 107(1):223–??, March 2020. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/1/223/5572662.

Woody:2022:OPS

[WPS22] S. Woody, O. H. M. Padilla, and J. G. Scott. Optimal postselection inference for sparse signals: a nonparametric empirical Bayes approach. Biometrika, 109(1):1–16, March 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article/
109/1/1/6154858.

Wang:2020:MFA

[WPTC20] Xuan Wang, Layla Parast, Lu Tian, and Tianxi Cai. Modelfree approach to quantifying the proportion of treatment effect explained by a surrogate marker. Biometrika, 107(1):107–??, March 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/1/107/5686746.

Wang:2022:ART

[WX22] Rui Wang and Wangli Xu. An approximate randomization test for the high-dimensional two-sample Behrens–Fisher problem under arbitrary covariances. Biometrika, 109(4):1117–1132, December 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/109/4/1117/6535701.

Wang:2020:MDA

[WZ20] Yixin Wang and Jose R. Zubizarreta. Minimal dispersion approximately balancing weights: asymptotic properties and practical considerations. Biometrika, 107(1):93–??, March 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/1/93/5602475.

Wang:2021:ELT

[WZRR21] Linbo Wang, Yuexia Zhang, Thomas S. Richardson, and James M. Robins. Estimation of local treatment effects under the binary instrumental variable model. Biometrika, 108 (4):881–894, December 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/108/4/881/6128502.

Xia:2022:DIM

[XC22] Fan Xia and Kwun Chuen Gary Chan. Decomposition, identification and multiply robust estimation of natural mediation effects with multiple mediators. Biometrika, 109(4):1085–1100, December 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/109/4/1085/6524619.

Xu:2022:PDA

[XL22] Jason Xu and Kenneth Lange. A proximal distance algorithm for likelihood-based sparse covariance estimation. Biometrika, 109 (4):1047–1066, December 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/109/4/1047/6529114.

Xie:2020:OBE

[XX20] Fangzheng Xie and Yanxun Xu. Optimal Bayesian estimation for random dot product graphs. Biometrika, 107(4):875–??, December 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/4/875/5867841.

Xu:2023:MPH

[XZL23] Yangjianchen Xu, Donglin Zeng, and D Y Lin. Marginal proportional hazards models for multivariate interval-censored data. Biometrika, 110(3):815–830, September 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/110/3/815/6794202.

Yoon:2020:SSC

[YCG20] Grace Yoon, Raymond J. Carroll, and Irina Gaynanova. Sparse semiparametric canonical correlation analysis for data of mixed types. Biometrika, 107(3):609–??, September 2020. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/3/609/5820553.

Yiu:2020:IUU

[YGT20] A. Yiu, R. J. B. Goudie, and B. D. M. Tom. Inference under unequal probability sampling with the Bayesian exponentially tilted empirical likelihood. Biometrika, 107(4):857–??, December 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/4/857/5841607.

Yang:2021:CIP

[YHF21] Tao Yang, Ying Huang, and Youyi Fong. Changepoint inference in the presence of missing covariates for principal surrogate evaluation in vaccine trials. Biometrika, 108(4):829–843, December 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/108/4/829/6029473.

Yu:2023:MSN

[YLYG23] Miao Yu, Wenbin Lu, Shu Yang, and Pulak Ghosh. A multiplicative structural nested mean model for zero-inflated outcomes. Biometrika, 110(2):519–536, June 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/110/2/519/6671840.

Yin:2022:MEM

[YMRW22] J. Yin, S. Markes, T. S. Richardson, and L. Wang. Multiplicative effect modelling: the general case. Biometrika, 109 (2):559–566, June 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/109/2/559/6481547.

Yang:2020:SES

[YPC20] S. Yang, K. Pieper, and F. Cools. Semiparametric estimation of structural failure time models in continuous-time processes. Biometrika, 107(1):123–??, March 2020. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/1/123/5609101.

Yu:2023:TKP

[YXZ23] Long Yu, Jiahui Xie, and Wang Zhou. Testing Kronecker product covariance matrices for high-dimensional matrix-variate data. Biometrika, 110(3):799–814, September 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/110/3/799/6832027.

Ying:2022:FSD

[YY22] Chao Ying and Zhou Yu. Fréchet sufficient dimension reduction for random objects. Biometrika, 109(4):975–992, December 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/109/4/975/6530280.

Ye:2022:IAT

[YYS22] Ting Ye, Yanyao Yi, and Jun Shao. Inference on the average treatment effect under minimization and other covariateadaptive randomization methods. Biometrika, 109(1):33–47, March 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/109/1/33/6157823.

Yan:2023:KTS

[YZ23] Jian Yan and Xianyang Zhang. Kernel two-sample tests in high dimensions: interplay between moment discrepancy and dimension-and-sample orders. Biometrika, 110(2):411–430, June 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/110/2/411/6670793.

Zhang:2022:HDS

[ZB22] Yuqian Zhang and Jelena Bradic. High-dimensional semisupervised learning: in search of optimal inference of the mean. Biometrika, 109(2):387–403, June 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/2/387/6370142.

Zheng:2021:FTA

[ZC21] Yao Zheng and Guang Cheng. Finite-time analysis of vector autoregressive models under linear restrictions. Biometrika, 108 (2):469–489, June 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/108/2/469/5895298.

Zhao:2022:RBC

[ZD22] Anqi Zhao and Peng Ding. Regression-based causal inference with factorial experiments: estimands, model specifications and design-based properties. Biometrika, 109(3):799–815, September 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/109/3/799/6409852.

Zhang:2020:GIM

[ZDS^{+}20] Han Zhang, Lu Deng, Mark Schiffman, Jing Qin, and Kai Yu. Generalized integration model for improved statistical inference by leveraging external summary data. Biometrika, 107 (3):689–??, September 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article-abstract/107/3/689/5820552.

Zhang:2021:HQR

[Zha21] Ting Zhang. High-quantile regression for tail-dependent time series. Biometrika, 108(1):113–126, March 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/108/1/113/
5876981.

Zhang:2022:AST

[Zha22a] Ting Zhang. Asymptotics of sample tail autocorrelations for tail-dependent time series: phase transition and visualization. Biometrika, 109(2):521–534, June 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/2/521/6322950.

Zhao:2022:GWI

[Zha22b] Haibing Zhao. General ways to improve false coverage rateadjusted selective confidence intervals. Biometrika, 109(1): 153–164, March 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/109/1/153/6137832.

Zhang:2021:LBS

[ZJB21] Weiping Zhang, Baisuo Jin, and Zhidong Bai. Learning block structures in u-statistic-based matrices. Biometrika, 108(4): 933–946, December 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.oup.

com/biomet/article/108/4/933/6007464.

Zeng:2021:MLE

[ZL21a] Donglin Zeng and D. Y. Lin. Maximum likelihood estimation for semiparametric regression models with panel count data. Biometrika, 108(4):947–963, December 2021. CODEN BIOKAX.

ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/108/4/947/5958114.

Zhang:2021:DET

[ZL21b] Y. Zhang and E. B. Laber. Discussion of ‘Estimating time-varying causal excursion effects in mobile health with binary outcomes’. Biometrika, 108(3):535–539, September 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/108/3/535/6350046. See

[QYK^{+}21a].

Zhang:2020:EMR

[ZLS20] X. Zhang, C. E. Lee, and X. Shao. Envelopes in multivariate regression models with nonlinearity and heteroscedasticity. Biometrika, 107(4):965–??, December 2020. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (elec-

tronic). URL http://academic.oup.com/biomet/article-
abstract/107/4/965/5858316.

Zhao:2022:DRC

[ZLWL22] Junlong Zhao, Xiumin Liu, Hansheng Wang, and Chenlei Leng. Dimension reduction for covariates in network data. Biometrika, 109(1):85–102, March 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/109/1/85/6131676.

Zapata:2022:PSF

[ZOP22] J. Zapata, S. Y. Oh, and A. Petersen. Partial separability and functional graphical models for multivariate Gaussian processes. Biometrika, 109(3):665–681, September 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/3/665/6380938.

Zhang:2022:UGO

[ZS22] Likun Zhang and Benjamin A. Shaby. Uniqueness and global optimality of the maximum likelihood estimator for the generalized extreme value distribution. Biometrika, 109(3):853–864, September 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article/109/3/853/6355019.

Zhou:2020:EII

[ZWZ20] Ruixuan Rachel Zhou, Liewei Wang, and Sihai Dave Zhao. Estimation and inference for the indirect effect in high-dimensional linear mediation models. Biometrika, 107(3):573–??, September 2020. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-

3510 (electronic). URL http://academic.oup.com/biomet/
article-abstract/107/3/573/5829472.

Zhang:2022:JLS

[ZXZ22] Xuefei Zhang, Gongjun Xu, and Ji Zhu. Joint latent space models for network data with high-dimensional node variables. Biometrika, 109(3):707–720, September 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/109/3/707/6470560.

Zhao:2022:HDL

[ZYH22] Peng Zhao, Yun Yang, and Qiao-Chu He. High-dimensional linear regression via implicit regularization. Biometrika, 109(4): 1033–1046, December 2022. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://academic.

oup.com/biomet/article/109/4/1033/6527189.

Zhou:2023:FLR

[ZYZ23] Hang Zhou, Fang Yao, and Huiming Zhang. Functional linear regression for discretely observed data: from ideal to reality. Biometrika, 110(2):381–393, June 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/110/2/381/6726182.

Zhou:2023:ORC

[ZZ23] Zheng Zhou and Yongdao Zhou. Optimal row-column designs. Biometrika, 110(2):537–549, June 2023. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/110/2/537/6659856.

Zhou:2021:CAF

[ZZC21] Huijuan Zhou, Xianyang Zhang, and Jun Chen. Covariate adaptive familywise error rate control for genome-wide association studies. Biometrika, 108(4):915–931, December 2021. CO-DEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic).

URL http://academic.oup.com/biomet/article/108/4/915/
6007465.

Zhou:2021:PPD

[ZZZ21] Wenzhuo Zhou, Ruoqing Zhu, and Donglin Zeng. A parsimonious personalized dose-finding model via dimension reduction. Biometrika, 108(3):643–659, September 2021. CODEN BIOKAX. ISSN 0006-3444 (print), 1464-3510 (electronic). URL http://

academic.oup.com/biomet/article/108/3/643/5930894.