The three tests for mlogit models
Three tests for mlogit models: specific methods for the Wald test and the likelihood ration test and a new function for the score test
scoretest(object, ...) ## S3 method for class 'mlogit' scoretest(object, ...) ## Default S3 method: scoretest(object, ...) ## S3 method for class 'mlogit' waldtest(object, ...) ## S3 method for class 'mlogit' lrtest(object, ...)
object |
an object of class |
... |
two kinds of arguments can be used. If |
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.
an object of class htest
.
Yves Croissant
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)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.