R: Control Values for gls Fit

glsControl {nlme}

R Documentation

Control Values for gls Fit

Description

The values supplied in the function call replace the defaults and a list with all possible arguments is returned. The returned list is used as the control argument to the gls function.

Usage

glsControl(maxIter, msMaxIter, tolerance, msTol, msVerbose,
           singular.ok, returnObject, apVar, .relStep,
           opt=c("nlminb", "optim"), optimMethod,
           minAbsParApVar, natural, sigma = NULL)

Arguments

`maxIter`	maximum number of iterations for the `gls` optimization algorithm. Default is 50.
`msMaxIter`	maximum number of iterations for the optimization step inside the `gls` optimization. Default is 50.
`tolerance`	tolerance for the convergence criterion in the `gls` algorithm. Default is 1e-6.
`msTol`	tolerance for the convergence criterion of the first outer iteration when `optim` is used. Default is 1e-7.
`msVerbose`	a logical value passed as the `trace` argument to `ms` (see documentation on that function). Default is `FALSE`.
`singular.ok`	a logical value indicating whether non-estimable coefficients (resulting from linear dependencies among the columns of the regression matrix) should be allowed. Default is `FALSE`.
`returnObject`	a logical value indicating whether the fitted object should be returned when the maximum number of iterations is reached without convergence of the algorithm. Default is `FALSE`.
`apVar`	a logical value indicating whether the approximate covariance matrix of the variance-covariance parameters should be calculated. Default is `TRUE`.
`.relStep`	relative step for numerical derivatives calculations. Default is `.Machine$double.eps^(1/3)`.
`opt`	the optimizer to be used, either `"nlminb"` (the current default) or `"optim"` (the previous default).
`optimMethod`	character - the optimization method to be used with the `optim` optimizer. The default is `"BFGS"`. An alternative is `"L-BFGS-B"`.
`minAbsParApVar`	numeric value - minimum absolute parameter value in the approximate variance calculation. The default is `0.05`.
`natural`	logical. Should the natural parameterization be used for the approximate variance calculations? Default is `TRUE`.
`sigma`	optionally a positive number to fix the residual error at. If `NULL`, as by default, or `0`, sigma is estimated.

Value

a list with components for each of the possible arguments.

Author(s)

José Pinheiro and Douglas Bates bates@stat.wisc.edu; the sigma option: Siem Heisterkamp and Bert van Willigen.

Examples

# decrease the maximum number iterations in the optimization call and
# request that information on the evolution of the ms iterations be printed
glsControl(msMaxIter = 20, msVerbose = TRUE)

[Package nlme version 3.1-131 Index]