LL_gaussian {gspcr}

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.

Author(s)

Edoardo Costantini, 2022