mclogit.control: Control Parameters for the Fitting Process

Description

mclogit.control returns a list of default parameters that control the fitting process of mclogit.

Usage

mclogit.control(epsilon = 1e-08,
                maxit = 25, trace=TRUE)
mmclogit.control(epsilon = 1e-08,
                 maxit = 25, trace=TRUE,
                 trace.inner=FALSE,
                 avoid.increase = FALSE,
                 break.on.increase = FALSE,
                 break.on.infinite = FALSE,
                 break.on.negative = FALSE,
                 inner.optimizer = "nlminb",
                 maxit.inner = switch(inner.optimizer,
                                      SANN          = 10000,
                                      `Nelder-Mead` = 500,
                                      100),
                 CG.type = 1,
                 NM.alpha = 1,
                 NM.beta = 0.5,
                 NM.gamma = 2.0,
                 SANN.temp = 10,
                 SANN.tmax = 10,
                 grtol = 1e-6,
                 xtol = 1e-8,
                 maxeval = 100,
                 gradstep = c(1e-6, 1e-8),
                 use.gradient = c("analytic","numeric"))

Value

A list.

Arguments

epsilon: positive convergence tolerance \(\epsilon\); the iterations converge when \(|dev - dev_{old}|/(|dev| + 0.1) < \epsilon\).
maxit: integer giving the maximal number of IWLS or PQL iterations.
trace: logical indicating if output should be produced for each iteration.
trace.inner: logical; indicating if output should be produced for each inner iteration of the PQL method.
avoid.increase: logical; should an increase of the deviance be avoided by step truncation?
break.on.increase: logical; should an increase of the deviance be avoided by stopping the algorithm?
break.on.infinite: logical; should an infinite deviance stop the algorithm instead of leading to step truncation?
break.on.negative: logical; should a negative deviance stop the algorithm?
inner.optimizer: a character string, one of "nlminb", "nlm", "ucminf", "Nelder-Mead", "BFGS", "CG", "L-BFGS-B", "SANN". See nlminb, nlm, ucminf, or optim.
maxit.inner: integer; the maximum number of inner iterations
CG.type: integer; the type argument passed to optim if "CG" is selected as inner optimizer.
NM.alpha: integer; the alpha argument passed to optim if "Nelder-Mead" is selected as inner optimizer.
NM.beta: integer; the beta argument passed to optim if "Nelder-Mead" is selected as inner optimizer.
NM.gamma: integer; the gamma argument passed to optim if "Nelder-Mead" is selected as inner optimizer.
SANN.temp: integer; the temp argument passed to optim if "SANN" is selected as inner optimizer.
SANN.tmax: integer; the tmax argument passed to optim if "SANN" is selected as inner optimizer.
grtol: numeric; the grtol control parameter for ucminf if "ucminf" is selected as inner optimizer.
xtol: numeric; the xtol control parameter for ucminf if "ucminf" is selected as inner optimizer.
maxeval: integer; the maxeval control parameter for ucminf if "ucminf" is selected as inner optimizer.
gradstep: a numeric vector of length; the gradstep control parameter for ucminf if "ucminf" is selected as inner optimizer.
use.gradient: a character string; whether the gradient should be computed analytically or whether a finite-difference approximation should be used.