clmm.control: Set control parameters for cumulative link mixed models
In ordinal: Regression Models for Ordinal Data

Description Usage Arguments Value Author(s) See Also

Set control parameters for cumulative link mixed models

clmm.control(method = c("nlminb", "ucminf", "model.frame"), ..., trace = 0,
maxIter = 50, gradTol = 1e-4, maxLineIter = 50,  useMatrix = FALSE,
innerCtrl = c("warnOnly", "noWarn", "giveError"),
checkRanef = c("warn", "error", "message"))

`method`	the optimizer used to maximize the marginal likelihood function.
`...`	control arguments passed on to the optimizer; see `ucminf` for details. `ucminf` for details.
`trace`	numerical, if > 0 information is printed about and during the outer optimization process, if < 0 information is also printed about the inner optimization process. Defaults to `0`.
`maxIter`	the maximum number of Newton updates of the inner optimization. `50`.
`gradTol`	the maximum absolute gradient of the inner optimization.
`maxLineIter`	the maximum number of step halfings allowed if a Newton(-Raphson) step over shoots during the inner optimization.
`useMatrix`	if `TRUE`, a general implementation of the Laplace approximation using the Matrix package is used, while if `FALSE` (default), a C implementation of the Laplace approximation valid only for models with a single random effects term is used when possible. `TRUE` is not valid for models fitted with quadrature methods.
`innerCtrl`	the use of warnings/errors if the inner optimization fails to converge.
`checkRanef`	the use of message/warning/error if there are more random effects than observations.