mclogit.control

positive convergence tolerance \(\epsilon\);
 the iterations converge when
 \(|dev - dev_{old}|/(|dev| + 0.1) &lt; \epsilon\).

epsilon

integer giving the maximal number of IWLS or PQL iterations.

maxit

logical indicating if output should be produced for each
 iteration.

trace

<code>mclogit.control</code> returns a list of default parameters
 that control the fitting process of <code>mclogit</code>.

Specification and estimation of conditional logit models of binary responses and multinomial counts is provided,
with or without alternative-specific random effects (random intercepts only, no random slopes yet).
The current implementation of the estimator for random effects variances uses a Laplace approximation (or PQL)
approach and thus should be used only if groups sizes are large.

mclogit.control: Control Parameters for the Fitting Process

Description

Usage

Arguments

Value