mlogit (version 1.1-2)

scoretest: The three tests for mlogit models

Description

Three tests for mlogit models: specific methods for the Wald test and the likelihood ration test and a new function for the score test

Usage

scoretest(object, ...)
# S3 method for mlogit
scoretest(object, ...)
# S3 method for default
scoretest(object, ...)
# S3 method for mlogit
waldtest(object, ...)
# S3 method for mlogit
lrtest(object, ...)

Value

an object of class `htest`.

Arguments

object

an object of class `mlogit` or a formula,

...

two kinds of arguments can be used. If `mlogit` arguments are introduced, initial model is updated using these arguments. If `formula` or other `mlogit` models are introduced, the standard behavior of [lmtest::waldtest()] and [lmtest::lrtest()] is followed.

Author

Yves Croissant

Details

The `scoretest` function and `mlogit` method for `waldtest` and `lrtest` from the `lmtest` package provides the infrastructure to compute the three tests of hypothesis for `mlogit` objects.

The first argument must be a `mlogit` object. If the second one is a fitted model or a formula, the behaviour of the three functions is the one of the default methods of `waldtest` and `lrtest`: the two models provided should be nested and the hypothesis tested is that the constrained model is the `right' model.

If no second model is provided and if the model provided is the constrained model, some specific arguments of `mlogit` should be provided to descibe how the initial model should be updated. If the first model is the unconstrained model, it is tested versus the `natural' constrained model; for example, if the model is a heteroscedastic logit model, the constrained one is the multinomial logit model.

Examples

library("mlogit")
library("lmtest")
data("TravelMode", package = "AER")
ml <- mlogit(choice ~ wait + travel + vcost, TravelMode,
             shape = "long", chid.var = "individual", alt.var = "mode")
hl <- mlogit(choice ~ wait + travel + vcost, TravelMode,
             shape = "long", chid.var = "individual", alt.var = "mode",
             method = "bfgs", heterosc = TRUE)
lrtest(ml, hl)
waldtest(hl)
scoretest(ml, heterosc = TRUE)