gaussian.loglik.g: Log likelihood function for linear regression using Zellners...

In FBMS: Flexible Bayesian Model Selection and Model Averaging

Log likelihood function for linear regression using Zellners g-prior

Description

Log likelihood function for linear regression using Zellners g-prior

Usage

gaussian.loglik.g(y, x, model, complex, mlpost_params = NULL)

Arguments

y	A vector containing the dependent variable
x	The matrix containing the precalculated features
model	The model to estimate as a logical vector
complex	A list of complexity measures for the features
mlpost_params	A list of parameters for the log likelihood, supplied by the user

Value

A list with the log marginal likelihood combined with the log prior (crit) and the posterior mode of the coefficients (coefs).

Examples

gaussian.loglik.g(rnorm(100), matrix(rnorm(100)), TRUE, list(oc=1))

FBMS documentation built on Sept. 13, 2025, 1:09 a.m.