auxVarCpp.RdGiven the specific inputs, determine auxiliary covariate values using a Gibbs sampling procedure.
auxVarCpp(tau, rho, nu, N, R, J, rho_mat, adjacency, cov_i, weights, group_lengths, group_functions)
| tau | A numeric vector for the intercept terms in the covariate model |
|---|---|
| rho | A numeric vector for the correlation terms in the covariate model |
| nu | A numberic vector for the neighbor terms in the covariate model |
| N | An integer indicating the size of the interconnected network |
| R | An integer indicating the number of iterations for the Gibbs |
| J | An integer for the number of covariates |
| rho_mat | A numeric matrix for rho terms |
| adjacency | A binary matrix indicating connected units |
| cov_i | A numeric matrix for observed covariate values (starting values for chain) |
| weights | A numeric vector indicating the number of neighbors for each node |
| group_lengths | An integer vector indicating the number of categories for each variable |
| group_functions | An integer vector indicating the type of variable |
A numeric matrix for auxiliary covariate values between [0,1]