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Prepare Z Array for C++ Consumption

prepare_Z_list.Rd

Converts a 4D array of exogenous covariates into a format optimized for C++ processing. RcppArmadillo handles 4D arrays most efficiently when decomposed into a list of 3D cubes.

Usage

prepare_Z_list(Z)

Arguments

Z

Array of exogenous covariates. Can be:

  • NULL: Returns empty list

  • 3D array (m x m x T): Single time-varying covariate

  • 4D array (m x m x q x T): Multiple covariates

Value

List of 3D arrays, where each element corresponds to one covariate across all time periods. Length equals q (number of covariates).

Details

This function handles the dimensional restructuring needed for computation in the C++ backend. The transformation preserves the covariate structure while enabling vectorized operations in Armadillo.

Input dimensions:

  • 3D array (m x m x T): Interpreted as single covariate (q=1)

  • 4D array (m x m x q x T): Multiple covariates

Output structure:

  • List of length q

  • Each element is an (m x m x T) array for one covariate

Examples

if (FALSE) { # \dontrun{
# Single covariate
Z_single <- array(rnorm(10*10*5), dim=c(10,10,5))
Z_list <- prepare_Z_list(Z_single)
length(Z_list)  # Returns 1

# Multiple covariates  
Z_multi <- array(rnorm(10*10*3*5), dim=c(10,10,3,5))
Z_list <- prepare_Z_list(Z_multi)
length(Z_list)  # Returns 3
} # }