The `vcov` method for `mlogit` objects extract the covariance matrix of the coefficients, the errors or the random parameters.
# S3 method for mlogit
vcov(
object,
what = c("coefficient", "errors", "rpar"),
subset = c("all", "iv", "sig", "sd", "sp", "chol"),
type = c("cov", "cor", "sd"),
reflevel = NULL,
...
)# S3 method for vcov.mlogit
print(x, ...)
# S3 method for vcov.mlogit
summary(object, ...)
# S3 method for summary.vcov.mlogit
print(
x,
digits = max(3, getOption("digits") - 2),
width = getOption("width"),
...
)
a `mlogit` object (and a `vcov.mlogit` for the summary method),
indicates which covariance matrix has to be extracted : the default value is `coefficients`, in this case, `vcov` behaves as usual. If `what` equals `errors` the covariance matrix of the errors of the model is returned. Finally, if `what` equals `rpar`, the covariance matrix of the random parameters are extracted,
the subset of the coefficients that have to be extracted (only relevant if `what` ` = "coefficients"`),
with this argument, the covariance matrix may be returned (the default) ; the correlation matrix with the standard deviation on the diagonal may also be extracted,
relevent for the extraction of the errors of a multinomial probit model ; in this case the covariance matrix is of error differences is returned and, with this argument, the alternative used for differentiation is indicated,
further arguments.
a `vcov.mlogit` or a `summary.vcov.mlogit` object,
the number of digits,
the width of the printing,
Yves Croissant
This new interface replaces the `cor.mlogit` and `cov.mlogit` functions which are deprecated.
[mlogit()] for the estimation of multinomial logit models.