Efficient Bayesian Modeling of Binary and Categorical Data in R: The UPG Package

In this vignette, we introduce the UPG package for efficient Bayesian inference in probit, logit, multinomial logit and binomial logit models. UPG offers a convenient estimation framework for balanced and imbalanced data settings where sampling efficiency is ensured through marginal data augmentatio...

Full description

Saved in:
Bibliographic Details
Published in:arXiv.org 2023-06
Main Authors: Zens, Gregor, Frühwirth-Schnatter, Sylvia, Wagner, Helga
Format: Article
Language:English
Subjects:
Algorithms
Bayesian analysis
Logit models
Markov chains
Parameter estimation
Production methods
Sampling
Statistical inference
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this vignette, we introduce the UPG package for efficient Bayesian inference in probit, logit, multinomial logit and binomial logit models. UPG offers a convenient estimation framework for balanced and imbalanced data settings where sampling efficiency is ensured through marginal data augmentation. UPG provides several methods for fast production of output tables and summary plots that are easily accessible to a broad range of users.
ISSN:2331-8422