Set control parameters for cumulative link models

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Description

Set control parameters for cumulative link models

Usage

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clm.control(method = c("Newton", "model.frame", "design", "ucminf", "nlminb",
   "optim"), ..., trace = 0L,
   maxIter = 100L, gradTol = 1e-06, maxLineIter = 15L, relTol = 1e-6,
   tol = sqrt(.Machine$double.eps), maxModIter = 5L,
   convergence = c("warn", "silent", "stop", "message"))

Arguments

method

"Newton" fits the model by maximum likelihood and "model.frame" cause clm to return the model.frame, "design" causes clm to return a list of design matrices etc. that can be used with clm.fit.

trace

numerical, if > 0 information is printed about and during the optimization process. Defaults to 0.

maxIter

the maximum number of Newton-Raphson iterations. Defaults to 100.

gradTol

the maximum absolute gradient; defaults to 1e-6.

maxLineIter

the maximum number of step halfings allowed if a Newton(-Raphson) step over shoots. Defaults to 10.

relTol

relative convergence tolerence: relative change in the parameter estimates between Newton iterations. Defaults to 1e-6.

tol

numerical tolerence on eigenvalues to determine negative-definiteness of Hessian. If the Hessian of a model fit is negative definite, the fitting algorithm did not converge. If the Hessian is singular, the fitting algorithm did converge albeit not to a unique optimum, so one or more parameters are not uniquely determined even though the log-likelihood value is.

maxModIter

the maximum allowable number of consecutive iterations where the Newton step needs to be modified to be a decent direction. Defaults to 5.

convergence

action to take if the fitting algorithm did not converge.

...

control arguments parsed on to ucminf, nlminb or optim.

Value

a list of control parameters.

Author(s)

Rune Haubo B Christensen

See Also

clm

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