control
argument to the nlme
function.nlmeControl(maxIter, pnlsMaxIter, msMaxIter, minScale,
tolerance, niterEM, pnlsTol, msTol,
returnObject, msVerbose, gradHess, apVar, .relStep,
minAbsParApVar = 0.05,
opt = c("nlminb", "nlm"), natural = TRUE, sigma = NULL, …)
nlme
optimization algorithm. Default is 50.PNLS
optimization step inside the nlme
optimization. Default is 7.nlm
optimization step inside the nlme
optimization. Default is 50.PNLS
step.
Default 0.001
.nlme
algorithm. Default is 1e-6
.PNLS
step. Default is 1e-3
.nlm
,
passed as the gradtol
argument to the function (see
documentation on nlm
). Default is 1e-7
. FALSE
.trace
argument to
nlm
(see documentation on that function). Default is
FALSE
.nlm
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
.TRUE
..Machine$double.eps^(1/3)
.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.nlminb
, where used (eval.max
and those from
abs.tol
down).nlme
, nlm
, optim
,
nlmeStruct
# decrease the maximum number iterations in the ms call and
# request that information on the evolution of the ms iterations be printed
nlmeControl(msMaxIter = 20, msVerbose = TRUE)
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