networkGibbsOuts1Cpp: Estimate overall network causal effect
In isabelfulcher/autognet: Estimation of causal network effects

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
)

`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