Likelihood Ratio Test for Nested GKw Models

Performs a likelihood ratio test to compare two nested Generalized Kumaraswamy regression models.

Usage

lrtest(object, object2)

Arguments

object: A fitted model object of class "gkwreg" (the restricted model).
object2: A fitted model object of class "gkwreg" (the full model).

Value

A list with class "htest" containing:

statistic: The LRT test statistic
parameter: Degrees of freedom for the test
p.value: P-value from the chi-squared distribution
method: Description of the test
data.name: Names of the compared models

Details

This function performs a likelihood ratio test (LRT) to compare two nested models. The test statistic is: $$LRT = 2(\ell_{\text{full}} - \ell_{\text{restricted}})$$ which follows a chi-squared distribution with degrees of freedom equal to the difference in the number of parameters.

The models must be nested (one is a special case of the other) and fitted to the same data for the test to be valid.

Author

Lopes, J. E.

Examples

# \donttest{
data(GasolineYield)

# Fit nested models
fit_restricted <- gkwreg(yield ~ temp, data = GasolineYield, family = "kw")
fit_full <- gkwreg(yield ~ batch + temp, data = GasolineYield, family = "kw")
#> Warning: NaNs produced

# Likelihood ratio test
lrtest(fit_restricted, fit_full)
#> 
#> 	Likelihood Ratio Test for Nested GKw Models
#> 
#> data:  fit_restricted vs fit_full
#> LRT = 113.04, df = 9, p-value < 2.2e-16
#> 
# }