UPG.Diag: MCMC Diagnostics for 'UPG.Probit', 'UPG.Logit', 'UPG.MNL' and...

In UPG: Efficient Bayesian Algorithms for Binary and Categorical Data Regression Models

MCMC Diagnostics for UPG.Probit, UPG.Logit, UPG.MNL and UPG.Binomial objects using coda

Description

UPG.Diag computes a number of MCMC diagnostics based on the Markov chains that are contained in the model output returned by UPG.

Usage

UPG.Diag(object = NULL)

Arguments

object

an object of class UPG.Probit, UPG.Logit, UPG.MNL or UPG.Binomial.

Value

Returns a list containing effective sample size, effective sampling rate and inefficiency factors for each coefficient. In addition, maximum, minimum and median of these measures are returned.

Author(s)

Gregor Zens

Examples

# estimate a probit model using example data
library(UPG)
data(lfp)
y = lfp[,1]
X = lfp[,-1]
results.probit = UPG(y = y, X = X, model = "probit")

# compute MCMC diagnostics
UPG.Diag(results.probit)

UPG documentation built on Nov. 4, 2023, 5:06 p.m.