Description Usage Arguments Value
Given the specific inputs, determine covariate values using a Gibbs sampling procedure.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | networkGibbsOutCovCpp(
tau,
rho,
nu,
ncov,
R,
N,
burnin,
rho_mat,
adjacency,
weights,
cov_mat,
group_lengths,
group_functions,
additional_nu
)
|
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 matrix 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 |
additional_nu |
An integer (0/1) specifying whether neighbor cross terms will be evaluated (i.e. non-zero) |
A list of numeric matrices that contain the covariate values and neighbor covariate values for each person at that specific point in the chain
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