The values supplied in the lmeControl() call replace the
defaults, and a list with all settings (i.e., values for
all possible arguments) is returned. The returned list is
used as the control argument to the lme function.
lmeControl(maxIter = 50, msMaxIter = 50, tolerance = 1e-6, niterEM = 25,
msMaxEval = 200,
msTol = 1e-7, msVerbose = FALSE,
returnObject = FALSE, gradHess = TRUE, apVar = TRUE,
.relStep = .Machine$double.eps^(1/3), minAbsParApVar = 0.05,
opt = c("nlminb", "optim"),
optimMethod = "BFGS", natural = TRUE,
sigma = NULL,
allow.n.lt.q = FALSE,
...)a list with components for each of the possible arguments.
maximum number of iterations for the lme
optimization algorithm. Default is 50.
maximum number of iterations
for the optimization step inside the lme optimization.
Default is 50.
tolerance for the convergence criterion in the
lme algorithm. Default is 1e-6.
number of iterations for the EM algorithm used to refine
the initial estimates of the random effects variance-covariance
coefficients. Default is 25.
maximum number of evaluations of the objective
function permitted for nlminb. Default is 200.
tolerance for the convergence criterion on the first
iteration when optim is used. Default is 1e-7.
a logical value passed as the trace argument to
nlminb or optim. Default is FALSE.
a logical value indicating whether the fitted
object should be returned with a warning (instead of an
error via stop()) when the maximum number of
iterations is reached without convergence of the algorithm. Default
is FALSE.
a logical value indicating whether numerical gradient
vectors and Hessian matrices of the log-likelihood function should
be used in the internal optimization. This option is only available
when the correlation structure (corStruct) and the variance
function structure (varFunc) have no "varying" parameters and
the pdMat classes used in the random effects structure are
pdSymm (general positive-definite), pdDiag (diagonal),
pdIdent (multiple of the identity), or
pdCompSymm (compound symmetry). Default is TRUE.
a logical value indicating whether the approximate
covariance matrix of the variance-covariance parameters should be
calculated. Default is TRUE.
relative step for numerical derivatives
calculations. Default is .Machine$double.eps^(1/3).
the optimizer to be used, either "nlminb" (the
default) or "optim".
character - the optimization method to be used with
the optim optimizer. The default is
"BFGS". An alternative is "L-BFGS-B".
numeric value - minimum absolute parameter value
in the approximate variance calculation. The default is 0.05.
a logical value indicating whether the pdNatural
parametrization should be used for general positive-definite matrices
(pdSymm) in reStruct, when the approximate covariance
matrix of the estimators is calculated. Default is TRUE.
optionally a positive number to fix the residual error at.
If NULL, as by default, or 0, sigma is estimated.
logical indicating if it is ok to have
less observations than random effects for each group. The default,
FALSE signals an error; if NA, such a situation only gives
a warning, as in nlme versions prior to 2019; if true, no message
is given at all.
José Pinheiro and Douglas Bates bates@stat.wisc.edu; the
sigma option: Siem Heisterkamp and Bert van Willigen.
# decrease the maximum number iterations in the ms call and
# request that information on the evolution of the ms iterations be printed
str(lCtr <- lmeControl(msMaxIter = 20, msVerbose = TRUE))
## This should always work:
do.call(lmeControl, lCtr)
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