Gradient of the HLM loglikelihood.

Gradient of the HLM loglikelihood.

chlm_grad(beta, gamma, y, delta, X, Z)

Arguments

beta	Mean parameter vector of length p.
gamma	Variance parameter vector of length q.
y	Vector of observations of length n.
delta	Optional logical vector of length n indicating the censorring status (TRUE: uncensored, FALSE: uncensored).
X	Mean covariate matrix of size n x p.
Z	Variance covariate matrix of size n x q.

Value

Vector of length p+q returning the gradient of the loglikelihood at the parameter values.