genBlockD: Generates a block of the random effects covariance matrix

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

Generates a block of the random effects covariance matrix

Description

Generates a block of the random effects covariance matrix

Usage

genBlockD(N_dim, N_func, func_def, N_var_func, col_id, N_par, cov_data, gamma)

Arguments

N_dim	Integer specifying the dimension of the matrix
N_func	Integer specifying the number of functions in the covariance function for this block.
func_def	Vector of integers of same length as 'func_def' specifying the function definition for each function.
N_var_func	Vector of integers of same length as 'func_def' specying the number of variables in the argument to the function
col_id	Matrix of integers of dimension length(func_def) x max(N_var_func) that indicates the respective column indexes of 'cov_data'
N_par	Vector of integers of same length as 'func_def' specifying the number of parameters in the function
cov_data	Matrix holding the data for the covariance matrix
gamma	Vector of covariance parameters specified in order they appear in the functions specified by 'func_def'

Details

Using the sparse representation of the random effects covariance matrix, constructs one of the blocks. The function definitions are: 1 indicator, 2 exponential, 3 AR-1, 4 squared exponential, 5 matern, 6 Bessel.

Value

A symmetric positive definite matrix

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