| nlmeControl {nlme} | R Documentation |
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 to the nlme function.
nlmeControl(maxIter, pnlsMaxIter, msMaxIter, minScale,
tolerance, niterEM, pnlsTol, msTol, msScale,
returnObject, msVerbose, gradHess, apVar, .relStep,
nlmStepMax = 100.0, minAbsParApVar = 0.05,
opt = c("nlminb", "nlm"), natural = TRUE)
maxIter |
maximum number of iterations for the nlme
optimization algorithm. Default is 50. |
pnlsMaxIter |
maximum number of iterations
for the PNLS optimization step inside the nlme
optimization. Default is 7. |
msMaxIter |
maximum number of iterations
for the nlm optimization step inside the nlme
optimization. Default is 50. |
minScale |
minimum factor by which to shrink the default step size
in an attempt to decrease the sum of squares in the PNLS step.
Default 0.001. |
tolerance |
tolerance for the convergence criterion in the
nlme 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. |
pnlsTol |
tolerance for the convergence criterion in PNLS
step. Default is 1e-3. |
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. |
returnObject |
a logical value indicating whether the fitted
object should be returned when the maximum number of iterations is
reached without convergence of the algorithm. Default is
FALSE. |
msVerbose |
a logical value passed as the trace argument to
nlm (see documentation on that function). Default is
FALSE. |
gradHess |
a logical value indicating whether numerical gradient
vectors and Hessian matrices of the log-likelihood function should
be used in the 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. |
apVar |
a logical value indicating whether the approximate
covariance matrix of the variance-covariance parameters should be
calculated. Default is TRUE. |
.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 |
minAbsParApVar |
numeric value - minimum absolute parameter value
in the approximate variance calculation. The default is 0.05. |
opt |
the optimizer to be used, either nlminb (the
default since (R 2.2.0) or nlm (the previous
default). |
natural |
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. |
a list with components for each of the possible arguments.
Jose Pinheiro Jose.Pinheiro@pharma.novartis.com and Douglas Bates bates@stat.wisc.edu
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)