lmn_loglik: Loglikelihood function for LMN models.

In mlysy/LMN: Inference for Linear Models with Nuisance Parameters

Loglikelihood function for LMN models.

Description

Loglikelihood function for LMN models.

Usage

lmn_loglik(Beta, Sigma, suff)

Arguments

Beta	A p x q matrix of regression coefficients (see lmn_suff()).
Sigma	A q x q matrix of error variances (see lmn_suff()).
suff	An object of class lmn_suff (see lmn_suff()).

Value

Scalar; the value of the loglikelihood.

Examples

# generate data
n <- 50
q <- 3
Y <- matrix(rnorm(n*q),n,q) # response matrix
X <- 1 # intercept covariate
V <- 0.5 # scalar variance specification
suff <- lmn_suff(Y, X = X, V = V) # sufficient statistics

# calculate loglikelihood
Beta <- matrix(rnorm(q),1,q)
Sigma <- diag(rexp(q))
lmn_loglik(Beta = Beta, Sigma = Sigma, suff = suff)

mlysy/LMN documentation built on March 25, 2022, 11:12 a.m.