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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