Research

Research Interests

time series

change-point analysis

invariance principles

change-point analysis

invariance principles

Publications and Preprints

A Note on the Existence of Solutions to a Stochastic Recurrence Equation.

Preprint, University of Utah (with I. Berkes and L. Horváth).

On Distinguishing Between Random Walks and Changes in the Mean Alternatives.

Preprint, University of Utah (with L. Horváth, M. Hušková and S. Ling).

Extreme Value Distribution of a Recursive-type Detector in a Linear Model.

Preprint, University of Utah (with M. Kühn).

Selection from a Stable Box.

Preprint, University of Utah (with I. Berkes and L. Horváth).

Long Memory versus Stochastic Trend.

Preprint, University of Utah (with L. Horváth and J. Steinebach).

Monitoring Shifts in Mean: Asymptotic Normality of Stopping Times.

Under revision (with L. Horváth, P. Kokoszka and J. Steinebach).

Near-Integrated Random Coefficient Autoregressive Time Series.

Under revision.

Change-Point Monitoring in Linear Models.

*Econometrics Journal, to appear (with L. Horváth, M. Hušková and P. Kokoszka).*

Discriminating between Level Shifts and Random Walks: a Delay Time Approach.

In:*Conference Proceedings, Prague Stochastics 2006* (Eds. M. Hušková and M. Janzura), 73-80

(with L. Horváth and Zs. Horváth).

A Limit Theorem for Mildly Explosive Autoregression with Stable Errors.

*Econometric Theory* , to appear (with L. Horváth).

Strong Approximation for the Sums of Squares of Augmented GARCH Sequences.

*Bernoulli* **12** (2006), 583-608 (with I. Berkes and L. Horváth).

Testing for Parameter Stability in RCA(1) Time Series.

*Journal of Statistical Planning and Inference* **136** (2006), 3070-3089.

Estimation in Random Coefficient Autoregressive Models.

*Journal of Time Series Analysis* **27** (2006), 61-76 (with L. Horváth and J. Steinebach).

Statistical Terminology.

In:*Encyclopedia of Actuarial Science, Vol. 3* (Eds. J.L. Teugels and B. Sundt).
Wiley, Chichester (2004), 1593-1596.

Strong Approximation for RCA(1) Time Series with Applications.

*Statistics & Probability Letters* **68** (2004), 369-382.

Delay Time in Sequential Detection of Change.

*Statistics & Probability Letters* **67** (2004), 221-231 (with L. Horváth).

Sequential Change-Point Analysis based on Invariance Principles.

Dissertation, University of Cologne (2004).

Approximations for the Maximum of a Vector-Valued Stochastic Process with Drift.

*Periodica Mathematica Hungarica* **47** (2003), 1-15 (with L. Horváth).

A Note on Estimating the Change-Point of a Gradually Changing Stochastic Process.

*Statistics & Probability Letters* **56** (2002), 177-191 (with J. Steinebach).

Preprint, University of Utah (with I. Berkes and L. Horváth).

On Distinguishing Between Random Walks and Changes in the Mean Alternatives.

Preprint, University of Utah (with L. Horváth, M. Hušková and S. Ling).

Extreme Value Distribution of a Recursive-type Detector in a Linear Model.

Preprint, University of Utah (with M. Kühn).

Selection from a Stable Box.

Preprint, University of Utah (with I. Berkes and L. Horváth).

Long Memory versus Stochastic Trend.

Preprint, University of Utah (with L. Horváth and J. Steinebach).

Monitoring Shifts in Mean: Asymptotic Normality of Stopping Times.

Under revision (with L. Horváth, P. Kokoszka and J. Steinebach).

Near-Integrated Random Coefficient Autoregressive Time Series.

Under revision.

Change-Point Monitoring in Linear Models.

Discriminating between Level Shifts and Random Walks: a Delay Time Approach.

In:

(with L. Horváth and Zs. Horváth).

A Limit Theorem for Mildly Explosive Autoregression with Stable Errors.

Strong Approximation for the Sums of Squares of Augmented GARCH Sequences.

Testing for Parameter Stability in RCA(1) Time Series.

Estimation in Random Coefficient Autoregressive Models.

Statistical Terminology.

In:

Strong Approximation for RCA(1) Time Series with Applications.

Delay Time in Sequential Detection of Change.

Sequential Change-Point Analysis based on Invariance Principles.

Dissertation, University of Cologne (2004).

Approximations for the Maximum of a Vector-Valued Stochastic Process with Drift.

A Note on Estimating the Change-Point of a Gradually Changing Stochastic Process.