Given the specific inputs, determine estimates of psi (overall) for each unit under some treatment regime using a Gibbs sampling procedure.

networkGibbsOuts1Cpp(cov_list, beta, p, ncov, R, N, adjacency, weights,
  burnin, average)

Arguments

cov_list

The output from networkGibbsOutCovCpp function

beta

A numeric vector for the parameters from the outcome model

p

A probability of treated units for the binomial treatment assignment draw

ncov

A numeric vector for the parameters from the outcome model

R

An integer indicating the number of iterations for the Gibbs

N

An integer indicating the size of the interconnected network

adjacency

A binary matrix indicating connected units

weights

A numeric vector indicating the number of neighbors for each node

burnin

The index to start evaluation as one would normally have for a burnin for a Bayesian computation.

average

An indicator of whether to evaluate the causal effects as an average of the R iterations

Value

A vector of length N containing the estimated value of psi for each person