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$double.eps^(1/3), minAbsParApVar = 0.05,
opt = c("nlminb", "optim"),
optimMethod = "BFGS", natural = TRUE,
sigma = NULL, …)
lme
optimization algorithm. Default is 50
.lme
optimization.
Default is 50
.lme
algorithm. Default is 1e-6
.25
.200
.optim
is used. Default is 1e-7
.FALSE
.corStruct
) and the variance
function structure (varFunc
) have no "varying" parameters and
the pdMat
classes used in the random effects structure are
pdSymm
(general positive-definite), pdDiag
(diagonal),
pdIdent
(multiple of the identity), or
pdCompSymm
(compound symmetry). Default is TRUE
.TRUE
..Machine$double.eps^(1/3)
.optim
optimizer. The default is
"BFGS"
. An alternative is "L-BFGS-B"
.0.05
.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
.NULL
, as by default, or 0
, sigma is estimated.lme
, nlminb
, optim
# 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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