mhurdle (version 1.3-1)

vuongtest: Vuoung test for non-nested models

Description

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

Usage

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

Value

an object of class "htest"

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,

true_model

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),

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)