Extracting posterior distributions from the linear predictor

extract_linear_predictor extracts the posterior distribution from the linear predictor

Usage

extract_linear_predictor(
  inla_model,
  n,
  d,
  Lk_eta,
  names_cat = names_cat,
  sim,
  verbose,
  cores
)

Arguments

inla_model

An object of class inla.

n

Number of observations.

d

Number of categories.

Lk_eta

Cholesky decomposition of the Hessian matrix.

names_cat

List generated with extract_formula.

sim

simulations for the function inla.posterior.sample

verbose

if TRUE all the computing process is shown. Default is FALSE

cores

number of cores to be used in the computations

Value

summary_linear_predictor List containing a summary of the marginal posterior distributions of the linear predictor.

marginals_linear_predictor List containing simulations of marginal posterior distributions of the linear predictor.

summary_alphas List containing a summary of the marginal posterior distributions of the alphas.

marginals_alphas List containing simulations of the marginal posterior distributions of the alphas.

summary_precision List containing a summary of the marginal posterior distributions of the precision.

marginals_precision List containing simulations of the marginal posterior distributions of the precision.

summary_means List containing a summary of the marginal posterior distributions of the means.

marginals_means List containing the simulations of the marginal posterior distributions of the means.

Author

Joaquín Martínez-Minaya jomarminaya@gmail.com