vcov.Rchoice: vcov method for Rchoice objects

In Rchoice: Discrete Choice (Binary, Poisson and Ordered) Models with Random Parameters

vcov method for Rchoice objects

Description

The vcov method for Rchoice objects extracts the covariance matrix of the coefficients or the random parameters. It also allows to get the standard errors for the variance-covariance matrix of the random parameters

Usage

## S3 method for class 'Rchoice'
vcov(
  object,
  what = c("coefficient", "ranp"),
  type = c("cov", "cor", "sd"),
  se = FALSE,
  digits = max(3, getOption("digits") - 2),
  ...
)

cov.Rchoice(x)

cor.Rchoice(x)

se.cov.Rchoice(x, sd = FALSE, digits = max(3, getOption("digits") - 2))

Arguments

object	a fitted model of class Rchoice,
what	indicates which covariance matrix has to be extracted. The default is coefficient. In this case the vcov behaves as usual. If what = "ranp" the covariance matrix of the random parameters is returned as default,
type	if the model is estimated with random parameters, then this argument indicates what matrix should be returned. If type = "cov", then the covariance matrix of the random parameters is returned; if type = "cor" then the correlation matrix of the random parameters is returned; if type = "sd" then the standard deviation of the random parameters is returned,
se	if TRUE and type = "cov" then the standard error of the covariance matrix of the random parameters is returned; if TRUE and type = "sd" the standard error of the standard deviation of the random parameter is returned. This argument if valid only if the model is estimated using correlated random parameters,
digits	number of digits,
...	further arguments
x	a fitted model of class Rchoice,
sd	if TRUE, then the standard deviation of the random parameters are returned,

Details

This new interface replaces the cor.Rchoice, cov.Rchoice and se.cov.Rchoice functions which are deprecated.

See Also

Rchoice for the estimation of discrete choice models with random parameters.

Rchoice documentation built on March 31, 2023, 11:13 p.m.