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)

Example output

Loading required package: Formula
Loading required package: truncreg
Loading required package: maxLik
Loading required package: miscTools

Please cite the 'maxLik' package as:
Henningsen, Arne and Toomet, Ott (2011). maxLik: A package for maximum likelihood estimation in R. Computational Statistics 26(3), 443-458. DOI 10.1007/s00180-010-0217-1.

If you have questions, suggestions, or comments regarding the 'maxLik' package, please use a forum or 'tracker' at maxLik's R-Forge site:
https://r-forge.r-project.org/projects/maxlik/
Loading required package: survival
Loading required package: texreg
Version:  1.36.23
Date:     2017-03-03
Author:   Philip Leifeld (University of Glasgow)

Please cite the JSS article in your publications -- see citation("texreg").

	Vuong Test (non-nested)

data:  dhm-ptm
z = -1.5427, p-value = 0.06145

mhurdle documentation built on May 2, 2019, 5:52 p.m.