LL_gaussian: Gaussian log-likelihood
In gspcr: Generalized Supervised Principal Component Regression

LL_gaussian

R Documentation

Gaussian log-likelihood

Description

Computes the gaussian (normal) log-likelihood of a vector of observed values given a trained linear regression model.

Usage

LL_gaussian(y, x, mod)

Arguments

`y`	numeric vector recording a continuous dependent variable.
`x`	data.frame (or matrix) containing predictor values.
`mod`	`glm` or `lm` object containing the estimated linear regression model.

Details

If x and y are equal to the data on which mod has been trained, this function returns the same result as the default logLink function. If x and y are new, the function returns the log-likelihood of the new data under the trained model.

Value

A list containing:

ll an atomic vector of length 1 containing the log-likelihood value.
sc an atomic vector containing the systematic component for the input x and mod.