# lmeControl

0th

Percentile

##### Control values for lme

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 in the lme function.

Keywords
models
##### Usage
lmeControl(maxIter, msMaxIter, tolerance, niterEM, msTol,
msScale, msVerbose, PQLmaxIt, .relStep,
nlmStepMax, optimizer,
EMverbose, analyticGradient, analyticHessian)
##### Arguments
maxIter
maximum number of iterations for the lme optimization algorithm. Default is 50.
msMaxIter
maximum number of iterations for the nlm optimization step inside the lme optimization. Default is 50.
tolerance
tolerance for the convergence criterion in the lme algorithm. Default is 1e-6.
niterEM
number of iterations for the EM algorithm used to refine the initial estimates of the random effects variance-covariance coefficients. Default is 25.
msTol
tolerance for the convergence criterion in nlm, passed as the rel.tolerance argument to the function (see documentation on nlm). Default is 1e-7.
msScale
scale function passed as the scale argument to the nlm function (see documentation on that function). Default is lmeScale.
msVerbose
a logical value passed as the trace argument to nlm (see documentation on that function). Default is getOption("verbose").
PQLmaxIt
maximum number of iterations for the PQL algorithm in GLMM.
.relStep
relative step for numerical derivatives calculations. Default is .Machine$double.eps^(1/3). nlmStepMax stepmax value to be passed to nlm. See nlm for details. Default is 100.0 optimizer the optimizer to be used - either "optim", the default, or "nlm" EMverbose a logical value indicating if verbose output should be produced during the EM iterations. Default is getOption("verbose". analyticGradient a logical value indicating if the analytic gradient of the objective should be used. This option is for testing purposes and would not normally be changed from the default. Default is TRUE. analyticHessian a logical value indicating if the analytic hessian of the objective should be calculated. This is an experimental feature and at present the default is FALSE. In future we may use the analytic Hessian in the optimization. ##### Value • a list with a component for each of the possible arguments. ##### synopsis lmeControl(maxIter = 50, msMaxIter = 50, tolerance = sqrt((.Machine$double.eps)), niterEM = 20, msTol = sqrt(.Machine$double.eps), msScale, msVerbose = getOption("verbose"), PQLmaxIt = 20, .relStep = (.Machine$double.eps)^(1/3), nlmStepMax = NULL, optimizer="nlm", EMverbose = getOption("verbose"), analyticGradient = TRUE, analyticHessian=FALSE))

lme, nlm, optim, lmeScale, GLMM

• lmeControl
##### Examples
# decrease the maximum number iterations in the ms call and
# request that information on the evolution of the ms iterations be printed
str(lmeControl(msMaxIter = 20, msVerbose = TRUE))
Documentation reproduced from package lme4, version 0.6-6, License: GPL version 2 or later

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