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Page 1 Documentation for MINPACK subroutine LMDIF1 Double precision version Argonne National Laboratory Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More March 1980 1. Purpose. The purpose of LMDIF1 is to minimize the sum of the squares of M nonlinear functions in N variables by a modification of the Levenberg-Marquardt algorithm. This is done by using the more general least-squares solver LMDIF. The user must provide a subroutine which calculates the functions. The Jacobian is then calculated by a forward-difference approximation. 2. Subroutine and type statements. SUBROUTINE LMDIF1(FCN,M,N,X,FVEC,TOL,INFO,IWA,WA,LWA) INTEGER M,N,INFO,LWA INTEGER IWA(N) DOUBLE PRECISION TOL DOUBLE PRECISION X(N),FVEC(M),WA(LWA) EXTERNAL FCN 3. Parameters. Parameters designated as input parameters must be specified on entry to LMDIF1 and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from LMDIF1. FCN is the name of the user-supplied subroutine which calculates the functions. FCN must be declared in an EXTERNAL statement in the user calling program, and should be written as follows. SUBROUTINE FCN(M,N,X,FVEC,IFLAG) INTEGER M,N,IFLAG DOUBLE PRECISION X(N),FVEC(M) ---------- CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. ---------- RETURN END The value of IFLAG should not be changed by FCN unless the user wants to terminate execution of LMDIF1. In this case set Page 2 IFLAG to a negative integer. M is a positive integer input variable set to the number of functions. N is a positive integer input variable set to the number of variables. N must not exceed M. X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. FVEC is an output array of length M which contains the functions evaluated at the output X. TOL is a nonnegative input variable. Termination occurs when the algorithm estimates either that the relative error in the sum of squares is at most TOL or that the relative error between X and the solution is at most TOL. Section 4 contains more details about TOL. INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. INFO = 0 Improper input parameters. INFO = 1 Algorithm estimates that the relative error in the sum of squares is at most TOL. INFO = 2 Algorithm estimates that the relative error between X and the solution is at most TOL. INFO = 3 Conditions for INFO = 1 and INFO = 2 both hold. INFO = 4 FVEC is orthogonal to the columns of the Jacobian to machine precision. INFO = 5 Number of calls to FCN has reached or exceeded 200*(N+1). INFO = 6 TOL is too small. No further reduction in the sum of squares is possible. INFO = 7 TOL is too small. No further improvement in the approximate solution X is possible. Sections 4 and 5 contain more details about INFO. IWA is an integer work array of length N. WA is a work array of length LWA. LWA is a positive integer input variable not less than Page 3 M*N+5*N+M. 4. Successful completion. The accuracy of LMDIF1 is controlled by the convergence parame- ter TOL. This parameter is used in tests which make three types of comparisons between the approximation X and a solution XSOL. LMDIF1 terminates when any of the tests is satisfied. If TOL is less than the machine precision (as defined by the MINPACK func- tion DPMPAR(1)), then LMDIF1 only attempts to satisfy the test defined by the machine precision. Further progress is not usu- ally possible. Unless high precision solutions are required, the recommended value for TOL is the square root of the machine precision. The tests assume that the functions are reasonably well behaved. If this condition is not satisfied, then LMDIF1 may incorrectly indicate convergence. The validity of the answer can be checked, for example, by rerunning LMDIF1 with a tighter toler- ance. First convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z, then this test attempts to guarantee that ENORM(FVEC) .LE. (1+TOL)*ENORM(FVECS), where FVECS denotes the functions evaluated at XSOL. If this condition is satisfied with TOL = 10**(-K), then the final residual norm ENORM(FVEC) has K significant decimal digits and INFO is set to 1 (or to 3 if the second test is also satis- fied). Second convergence test. If D is a diagonal matrix (implicitly generated by LMDIF1) whose entries contain scale factors for the variables, then this test attempts to guarantee that ENORM(D*(X-XSOL)) .LE. TOL*ENORM(D*XSOL). If this condition is satisfied with TOL = 10**(-K), then the larger components of D*X have K significant decimal digits and INFO is set to 2 (or to 3 if the first test is also satis- fied). There is a danger that the smaller components of D*X may have large relative errors, but the choice of D is such that the accuracy of the components of X is usually related to their sensitivity. Third convergence test. This test is satisfied when FVEC is orthogonal to the columns of the Jacobian to machine preci- sion. There is no clear relationship between this test and the accuracy of LMDIF1, and furthermore, the test is equally well satisfied at other critical points, namely maximizers and saddle points. Also, errors in the functions (see below) may result in the test being satisfied at a point not close to the Page 4 minimum. Therefore, termination caused by this test (INFO = 4) should be examined carefully. 5. Unsuccessful completion. Unsuccessful termination of LMDIF1 can be due to improper input parameters, arithmetic interrupts, an excessive number of func- tion evaluations, or errors in the functions. Improper input parameters. INFO is set to 0 if N .LE. 0, or M .LT. N, or TOL .LT. 0.D0, or LWA .LT. M*N+5*N+M. Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by LMDIF1. In this case, it may be possible to remedy the situation by not evalu- ating the functions here, but instead setting the components of FVEC to numbers that exceed those in the initial FVEC, thereby indirectly reducing the step length. The step length can be more directly controlled by using instead LMDIF, which includes in its calling sequence the step-length-governing parameter FACTOR. Excessive number of function evaluations. If the number of calls to FCN reaches 200*(N+1), then this indicates that the routine is converging very slowly as measured by the progress of FVEC, and INFO is set to 5. In this case, it may be help- ful to restart LMDIF1, thereby forcing it to disregard old (and possibly harmful) information. Errors in the functions. The choice of step length in the for- ward-difference approximation to the Jacobian assumes that the relative errors in the functions are of the order of the machine precision. If this is not the case, LMDIF1 may fail (usually with INFO = 4). The user should then use LMDIF instead, or one of the programs which require the analytic Jacobian (LMDER1 and LMDER). 6. Characteristics of the algorithm. LMDIF1 is a modification of the Levenberg-Marquardt algorithm. Two of its main characteristics involve the proper use of implicitly scaled variables and an optimal choice for the cor- rection. The use of implicitly scaled variables achieves scale invariance of LMDIF1 and limits the size of the correction in any direction where the functions are changing rapidly. The optimal choice of the correction guarantees (under reasonable conditions) global convergence from starting points far from the solution and a fast rate of convergence for problems with small residuals. Timing. The time required by LMDIF1 to solve a given problem Page 5 depends on M and N, the behavior of the functions, the accu- racy requested, and the starting point. The number of arith- metic operations needed by LMDIF1 is about N**3 to process each evaluation of the functions (one call to FCN) and M*(N**2) to process each approximation to the Jacobian (N calls to FCN). Unless FCN can be evaluated quickly, the tim- ing of LMDIF1 will be strongly influenced by the time spent in FCN. Storage. LMDIF1 requires M*N + 2*M + 6*N double precision sto- rage locations and N integer storage locations, in addition to the storage required by the program. There are no internally declared storage arrays. 7. Subprograms required. USER-supplied ...... FCN MINPACK-supplied ... DPMPAR,ENORM,FDJAC2,LMDIF,LMPAR, QRFAC,QRSOLV FORTRAN-supplied ... DABS,DMAX1,DMIN1,DSQRT,MOD 8. References. Jorge J. More, The Levenberg-Marquardt Algorithm, Implementation and Theory. Numerical Analysis, G. A. Watson, editor. Lecture Notes in Mathematics 630, Springer-Verlag, 1977. 9. Example. The problem is to determine the values of x(1), x(2), and x(3) which provide the best fit (in the least squares sense) of x(1) + u(i)/(v(i)*x(2) + w(i)*x(3)), i = 1, 15 to the data y = (0.14,0.18,0.22,0.25,0.29,0.32,0.35,0.39, 0.37,0.58,0.73,0.96,1.34,2.10,4.39), where u(i) = i, v(i) = 16 - i, and w(i) = min(u(i),v(i)). The i-th component of FVEC is thus defined by y(i) - (x(1) + u(i)/(v(i)*x(2) + w(i)*x(3))). C ********** C C DRIVER FOR LMDIF1 EXAMPLE. C DOUBLE PRECISION VERSION C Page 6 C ********** INTEGER J,M,N,INFO,LWA,NWRITE INTEGER IWA(3) DOUBLE PRECISION TOL,FNORM DOUBLE PRECISION X(3),FVEC(15),WA(75) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH FIT. C X(1) = 1.D0 X(2) = 1.D0 X(3) = 1.D0 C LWA = 75 C C SET TOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C TOL = DSQRT(DPMPAR(1)) C CALL LMDIF1(FCN,M,N,X,FVEC,TOL,INFO,IWA,WA,LWA) FNORM = ENORM(M,FVEC) WRITE (NWRITE,1000) FNORM,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // 5X,3D15.7) C C LAST CARD OF DRIVER FOR LMDIF1 EXAMPLE. C END SUBROUTINE FCN(M,N,X,FVEC,IFLAG) INTEGER M,N,IFLAG DOUBLE PRECISION X(N),FVEC(M) C C SUBROUTINE FCN FOR LMDIF1 EXAMPLE. C INTEGER I DOUBLE PRECISION TMP1,TMP2,TMP3 DOUBLE PRECISION Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4D-1,1.8D-1,2.2D-1,2.5D-1,2.9D-1,3.2D-1,3.5D-1,3.9D-1, * 3.7D-1,5.8D-1,7.3D-1,9.6D-1,1.34D0,2.1D0,4.39D0/ C Page 7 DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END Results obtained with different compilers or machines may be slightly different. FINAL L2 NORM OF THE RESIDUALS 0.9063596D-01 EXIT PARAMETER 1 FINAL APPROXIMATE SOLUTION 0.8241057D-01 0.1133037D+01 0.2343695D+01