predict_pg_mvgp_univariate_mra: Bayesian Polya-gamma regression prediction
In jtipton25/pgR: Bayesian Polya-Gamma Regression

predict_pg_mvgp_univariate_mra

R Documentation

Bayesian Polya-gamma regression prediction

this function generates predictions from the Bayesian multinomial regression using Polya-gamma data augmentation

predict_pg_mvgp_univariate_mra(
  out,
  X,
  X_pred,
  locs,
  locs_pred,
  n_cores = 1L,
  progress = TRUE,
  verbose = FALSE
)

`out`	is a list of MCMC outputs from pgSPLM
`X`	is a n x p matrix of covariates at the observed locations.
`X_pred`	is a n_{pred} x p matrix of covariates at the locations where predictions are to be made.
`locs`	is a n x 2 matrix of locations where observations were taken.
`locs_pred`	is a n_pred x 2 matrix of locations where predictions are to be made.
`n_cores`	is the number of cores for parallel computation using openMP.
`progress`	is a logicial input that determines whether to print a progress bar.
`verbose`	is a logicial input that determines whether to print more detailed messages.