cp_LRT: Compute likelihood ratio test

In gspcr: Generalized Supervised Principal Component Regression

Compute likelihood ratio test

Description

Computes the likelihood ratio expressed as a difference between the log-likelihoods of observed data under two nested competing models.

Usage

cp_LRT(ll_restricted, ll_full)

Arguments

ll_restricted	numeric vector of length 1 (or an object of class 'logLik') storing the log-likelihood of the observed data under the restricted model
ll_full	numeric vector of length 1 (or an object of class 'logLik') storing the log-likelihood of the observed data under the full model

Details

Note that:

• The full model is always the model with more estimated parameters, the model with more predictor variables.

• The restricted model is the model with fewer estimated parameters.

• The restricted model must be nested within the full model.

Value

numeric vector of length 1 storing the likelihood ratio test statistic

Author(s)

Edoardo Costantini, 2023

Examples

# Fit a nested model
nested <- glm(mpg ~ cyl + disp, data = mtcars)

# Fit a complex model
complex <- glm(mpg ~ cyl + disp + hp + am, data = mtcars)

# Compute log-likelihood statistic with your function
LRT_M <- cp_LRT(
    ll_restricted = logLik(nested),
    ll_full = logLik(complex)
)

gspcr documentation built on May 29, 2024, 2:44 a.m.