BayesSAE (version 1.0-2)

summary.BayesSAE: Extract Information from Object BayesSAE

Description

Methods for extracting information from fitted simplex regression model objects of class "BayesSAE"

Usage

# S3 method for BayesSAE
summary(object, HB = TRUE, ...)
MCMC(object, ...)

Arguments

object

fitted model object of class "BayesSAE"

HB

logical variable indication whether Rao-Blackwellization of theta (HB = TRUE) or posterior mean of theta (HB = FALSE) should be included. See Rao (2003) for details

...

currently not used

Value

These functions aim to extract information from the object of class "BayesSAE". Posterior means as and quantiles of regression coefficients as well as variance of residuals are included in the summary output. Function mcmc provides the object of class mcmc in the coda package for posterior diagnosis.

References

Rao, J. N. K. (2003) Small Area Estimation. John Wiley and Sons.

Examples

# NOT RUN {
# load data set
data(SAIPE)

# obtain posterior draws
result <- BayesSAE(SACPR~SNAPR+CenPR+CPER|Vardir, data = SAIPE, mcmc = 5000)

# summary information
summary(result)
# }