lm.logpost.bas: Log likelihood function for Gaussian regression with...

In FBMS: Flexible Bayesian Model Selection and Model Averaging

Log likelihood function for Gaussian regression with parameter priors from BAS package

Description

This is a placeholder version of the function. It falls back to gaussian.loglik.g and raises a warning if the full function is not loaded.

Usage

lm.logpost.bas(y, x, model, complex, mlpost_params = NULL)

Arguments

y	A vector containing the dependent variable
x	The matrix containing the precalculated features
model	A logical vector indicating which features are included in the model
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 approximate log marginal likelihood combined with the log prior (crit) and the posterior mode of coefficients (coefs)

Examples

lm.logpost.bas(rnorm(100), cbind(1, matrix(rnorm(100))), c(TRUE, TRUE), list(oc = 1))

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