extract_median_95CrI_descriptives_inla: Extraction of median and the equi-tailed 95% CrI from an INLA...

In hunansona/ed4bhm: Empirical Determinacy for Bayesian Hierarchical Models

Extraction of median and the equi-tailed 95% CrI from an INLA object

Description

This function takes an INLA object as input and extracts the median and the equi-tailed 95% CrI of all the model parameters.

Usage

extract_median_95CrI_descriptives_inla(inla.object, dz, diff.logdens)

Arguments

inla.object	character string, the name of the INLA object fitted in R-INLA
dz	Step length in the standardized scale used in the construction of the grid, default 0.75.
diff.logdens	The difference of the log.density for the hyperpameters to stop numerical integration using int.strategy='grid'. Default 15.

Details

The returned matrix has three columns with names "0.025quant", "0.5quant" and "0.975quant" for the median and the equi-tailed 95% CrI of the marginal posterior distributions and has as many rows as there are parameters in the model.

Value

numerical matix

See Also

inla

Examples

data(eight_schools)
#prior settings
mean_mu<-0
prec_mu<-1/(4^2) 
prec_tau<-1/(5^2)

library(INLA)
HN.prior = "expression:
  tau0 =  1/(5^2);
  sigma = exp(-theta/2);
  log_dens = log(2) - 0.5 * log(2 * pi) + 0.5 * log(tau0);
  log_dens = log_dens - 0.5 * tau0 * sigma^2;
  log_dens = log_dens - log(2) - theta / 2;
  return(log_dens);
"

formula.8schools.HN <- y ~ 1+f(schooln, model="iid", 
                                      hyper = list(prec = list(prior = HN.prior)))

# INLA uses the centered parametrization of the 8 schools model by default
fit.inla.8schools <- inla(formula.8schools.HN,
                                data = eight_schools,
                                family = "gaussian",
                                scale = eight_schools$prec,
                                control.family = list(hyper=list(prec=list(initial = log(1), fixed=TRUE))),
                                control.fixed = list(mean.intercept=mean_mu, prec.intercept=prec_mu),
                                control.compute=list(hyperpar=TRUE),
                                num.threads=1)

descriptives_median_95CrI_inla_8schools <- extract_median_95CrI_descriptives_inla(inla.obj = 
                                                  fit.inla.8schools)

hunansona/ed4bhm documentation built on June 15, 2022, 6:42 p.m.