BayesGOF (version 4.0)

DS.posterior.reduce: Posterior Expectation and Modes of DS object

Description

A function that determines the posterior expectations \(E(\theta_0 | y_0)\) and posterior modes for a set of observed data.

Usage

DS.posterior.reduce(DS.GF.obj, exposure)

Arguments

DS.GF.obj

Object resulting from running DS.prior function on a data set.

exposure

In the case of the Poisson family with exposure, represents the exposure values for the count data.

Value

Returns \(k \times 4\) matrix with the columns indicating PEB mean, DS mean, PEB mode, and DS modes for \(k\) observations in the data set.

References

Mukhopadhyay, S. and Fletcher, D., 2018. "Bayesian Modeling via Goodness-of-Fit," Technical report, https://arxiv.org/abs/1802.00474 .

Examples

# NOT RUN {
data(rat)
rat.start <- gMLE.bb(rat$y, rat$n)$estimate
rat.ds <- DS.prior(rat, max.m = 4, rat.start, family = "Binomial")
DS.posterior.reduce(rat.ds)
# }