gaussian.loglik {FBMS}

Log likelihood function for gaussian regression with a prior p(m)=r*sum(total_width).

Description

Log likelihood function for gaussian regression with a prior p(m)=r*sum(total_width).

Usage

gaussian.loglik(y, x, model, complex, params)

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

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(rnorm(100), matrix(rnorm(100)), TRUE, list(oc = 1), NULL)