mc_matrix_linear_predictor: Matrix Linear Predictor

In mcglm: Multivariate Covariance Generalized Linear Models

Matrix Linear Predictor

Description

Compute the matrix linear predictor. It is an internal function, however, since the concept of matrix linear predictor was proposed recently. I decided let this function visible to the interested reader gets some feeling about how it works.

Usage

mc_matrix_linear_predictor(tau, Z)

Arguments

tau	a numeric vector of dispersion parameters.
Z	a list of known matrices.

Details

Given a list with a set of known matrices (Z_0,...,Z_D) the function
mc_matrix_linear_predictor returns U = τ_0 Z_0 + ... + τ_D Z_D.

Value

A matrix.

Author(s)

Wagner Hugo Bonat, [e-mail]

Source

Bonat, W. H. (2018). Multiple Response Variables Regression Models in R: The mcglm Package. Journal of Statistical Software, 84(4):1–30.

Bonat, W. H. and Jorgensen, B. (2016) Multivariate covariance generalized linear models. Journal of Royal Statistical Society - Series C 65:649–675.

See Also

mc_id, mc_dist, mc_ma, mc_rw, mc_mixed and mc_car.

Examples

require(Matrix)
Z0 <- Diagonal(5, 1)
Z1 <- Matrix(rep(1,5)%*%t(rep(1,5)))
Z <- list(Z0, Z1)
mc_matrix_linear_predictor(tau = c(1,0.8), Z = Z)

mcglm documentation built on Sept. 16, 2022, 1:06 a.m.