R: Control Parameters for 'logistf'

logistf.control {logistf} | R Documentation

## Control Parameters for `logistf`

### Description

Sets parameters for Newton-Raphson iteration in Firth's penalized-likelihood logistic regression

### Usage

    logistf.control(maxit = 25, maxhs = 5, maxstep = 5, lconv = 1e-05, gconv = 1e-05,
        xconv = 1e-05, collapse=TRUE)

### Arguments

`maxit` | the maximum number of iterations
`maxhs` | the maximum number of step-halvings in one iteration. The increment of the beta vector within one iteration is divided by 2 if the new beta leads to a decrease in log likelihood.
`maxstep` | specifies the maximum step size in the beta vector within one iteration.
`lconv` | specifies the convergence criterion for the log likelihood.
`gconv` | specifies the convergence criterion for the first derivative of the log likelihood (the score vector).
`xconv` | specifies the convergence criterion for the parameter estimates.
`collapse` | if TRUE, evaluates all unique combinations of x and y and collapses data set. This may save computing time with large data sets with only categorical (binary) covariates.

### Details

`logistf.control()` is used by `logistf` and `logistftest` to set control parameters to default values. Different values can be specified, e. g., by `logistf(...,` `control=` `logistf.control(maxstep=1))`.

### Value

`maxit` | the maximum number of iterations
`maxhs` | the maximum number of step-halvings in one iteration. The increment of the beta vector within one iteration is divided by 2 if the new beta leads to a decrease in log likelihood.
`maxstep` | specifies the maximum step size in the beta vector within one iteration.
`lconv` | specifies the convergence criterion for the log likelihood.
`gconv` | specifies the convergence criterion for the first derivative of the log likelihood (the score vector).
`xconv` | specifies the convergence criterion for the parameter estimates.
`collapse` | if TRUE, evaluates all unique combinations of x and y and collapses data set.

### Author(s)

Georg Heinze

### Examples

    data(sexagg)
    fit2<-logistf(case ~ age+oc+vic+vicl+vis+dia, data=sexagg, weights=COUNT,
       control=logistf.control(maxstep=1))
    summary(fit2)

[Package logistf version 1.23 Index]