[R-pkgs] new version of minpack.lm

From: Katharine Mullen <kate_at_few.vu.nl>
Date: Thu, 13 Mar 2008 16:23:45 +0100 (CET)


The package minpack.lm allows nonlinear regression problems to be addressed with a modification of the Levenberg-Marquardt algorithm based on the implementation of 'lmder' and 'lmdif' in MINPACK. Version 1.0-8 of the package is now available on CRAN.

Changes in version 1.0-8 include:

    o possibility to obtain standard error estimates on the parameters       via new methods for the generic functions 'summary' and 'vcov'

    o possibility to extract other information via new methods for the

      generic functions 'coef', 'deviance', 'df.residual', 'print',
      and 'residuals'

    o the argument 'control' of 'nls.lm' now defaults to

'nls.lm.control()'; 'nls.control.lm' allows a maximum number of
iterations to be specified; when the element 'nprint' of the
'control' argument of a call to 'nls.lm' is an integer greater
than 0, the residual sum of squares is now included in the information printed every 'nprint' iterations ` o the list returned by 'nls.lm' includes elements 'niter' and
'deviance' that represent the number of iterations performed and
the residual sum of squares, respectively

side-note on Levenberg-Marquardt (LM) versus Gauss-Newton (GN): There was some discussion
(http://finzi.psych.upenn.edu/R/Rhelp02a/archive/108758.html) on Rhelp regarding whether one comes across real-world problems in which LM performs better than GN. I have been seeing such problems recently in some applications where GN as implemented in 'nls' reduces the step to a very small value, resulting in little change in the residual sum of squares from the starting values, whereas both NL2SOL applied via 'nls' called with 'algorithm="port"' or LM as implemented in 'minpack.lm::nls.lm' significantly reduce the RSS. The implementation of NL2SOL is slower by a significant factor on these problems as compared to either the GN or LM implementations, making use of 'minpack.lm::nls.lm' attractive. Note that these problems may be considered pathological; there are issues with near collinearity of columns of the Jacobian and with the assumption that the residuals are Gaussian.

Kate Mullen
Timur Elzhov



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