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Last data update: 2014.03.03

R: Vuoung test for non-nested models

vuongtest

R Documentation

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"),
          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.

Examples

data("tobin", package = "survival")
# selection double hurdle model
model110i <- mhurdle(durable ~ age |  quant | 0, tobin,  dist = "n")
# double-hurdle p-tobit
model011i <- mhurdle(durable ~ 0 |  quant | age, tobin,  dist = "n")
# Vuong test for strictly non-nested models
vuongtest(model011i, model110i)