networkGibbsOutCovCpp.Rd
Given the specific inputs, determine covariate values using a Gibbs sampling procedure.
networkGibbsOutCovCpp(tau, rho, nu, ncov, R, N, burnin, rho_mat, adjacency, weights, cov_mat, group_lengths, group_functions)
tau | A numeric vector for the intercept terms in the covariate model |
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rho | A numeric vector for the correlation terms in the covariate model |
nu | A numberic vector for the neighbor terms in the covariate model |
ncov | An integer for the number of covariates |
R | An integer indicating the number of iterations for the Gibbs |
N | An integer indicating the size of the interconnected network |
burnin | An integer indicating when to start saving values in the chain |
rho_mat | A numeric matrix for rho terms |
adjacency | A binary matrix indicating connected units |
weights | A numeric vector indicating the number of neighbors for each node |
cov_mat | A numeric matrix for starting values for each covariate |
group_lengths | An integer vector indicating the number of categories for each variable |
group_functions | An integer vector indicating the type of variable |
A list of numeric matrices that contain the covariate values and neighbor covariate values for each person at that specific point in the chain