vuongtest: Vuoung test for non-nested models

In mhurdle: Multiple Hurdle Tobit Models

Description

The Vuong test is suitable to discriminate between two non-nested models.

Usage

vuongtest(
  x,
  y,
  type = c("non-nested", "nested", "overlapping"),
  hyp = FALSE,
  variance = c("centered", "uncentered"),
  matrix = c("large", "reduced")
)

Arguments

x	a first fitted model of class "mhurdle",
y	a second fitted model of class "mhurdle",
type	the kind of test to be computed,
hyp	a boolean, TRUE if one of the models is asumed to be the true model,
variance	the variance is estimated using the centered or uncentered expression,
matrix	the W matrix can be computed using the general expression large or the reduced matrix reduced (only relevant for the nested case),

Value

an object of class "htest"

References

Vuong Q.H. (1989) Likelihood ratio tests for model selection and non-nested hypothesis, Econometrica, vol.57(2), pp.307-33.

See Also

vuong in package pscl.

Examples

data("Interview", package = "mhurdle")
# dependent double hurdle model
dhm <- mhurdle(vacations ~ car + size | linc + linc2 | 0, Interview,
              dist = "ln", h2 = TRUE, method = "bhhh", corr = TRUE)

# a double hurdle p-tobit model
ptm <- mhurdle(vacations ~ 0 | linc + linc2 | car + size, Interview,
              dist = "ln", h2 = TRUE, method = "bhhh", corr = TRUE)
vuongtest(dhm, ptm)

mhurdle documentation built on Dec. 11, 2021, 9:21 a.m.