l_lik_hess: Optimises the log-likelihood of the observations conditional...

In samuel-watson/glmmr: Design and analysis for generalised linear mixed models in R

Optimises the log-likelihood of the observations conditional on the random effects

Description

Optimises the log-likelihood of the observations conditional on the random effects

Usage

l_lik_hess(Z, X, y, u, family, link, start, lower, upper, trace, tol = 1e-04)

Arguments

Z	Matrix Z of the GLMM
X	Matrix X of the GLMM
y	Vector of observations
u	Matrix of samples of the random effects. Each column is a sample.
family	Character specifying the family
link	Character specifying the link function
start	Vector of starting values for the optimisation
lower	Vector of lower bounds for the model parameters
upper	Vector of upper bounds for the model parameters
trace	Integer indicating what to report to the console, 0= nothing, 1-3=detailed output

Value

A vector of parameters that maximise the log likelihood

samuel-watson/glmmr documentation built on July 27, 2022, 10:30 p.m.