A Pólya–Gamma sampler for a generalized logistic regression

DOI10.1080/00949655.2021.1910947OpenAlexW3154192862MaRDI QIDQ3389646

Fabrizio Leisen, Luca Rossini, Luciana Dalla Valle, Weixuan Zhu

Publication date: 23 March 2022

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2021.1910947

zbMATH Keywords

Bayesian inferencegeneralized logistic regressionPólya-gamma samplerrecidivism data

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• CODA
• BayesLogit

Cites Work

• The Pólya-gamma Gibbs sampler for Bayesian logistic regression is uniformly ergodic
• Slice sampling. (With discussions and rejoinder)
• An approximate likelihood perspective on ABC methods
• A theoretical comparison of the data augmentation, marginal augmentation and PX-DA algorithms
• Handbook of Markov Chain Monte Carlo
• The Calculation of Posterior Distributions by Data Augmentation
• Seeking efficient data augmentation schemes via conditional and marginal augmentation
• Parameter Expansion for Data Augmentation
• Bayesian analysis of immigration in Europe with generalized logistic regression
• A note on the posterior inference for the Yule–Simon distribution
• Bayesian Analysis of Binary and Polychotomous Response Data
• Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables
• Bayesian auxiliary variable models for binary and multinomial regression

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