Bayesian computation for logistic regression

DOI10.1016/J.CSDA.2004.04.009zbMath1429.62095OpenAlexW2058849009MaRDI QIDQ957166

Pieter C. N. Groenewald, Lucky Mokgatlhe

Publication date: 26 November 2008

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2004.04.009

zbMATH Keywords

Bayes factorsGibbs samplingdata augmentationordinal datalogit modelpolychotomous response

Mathematics Subject Classification ID

Bayesian inference (62F15) Generalized linear models (logistic models) (62J12)

Related Items (3)

A simulation study to compare reference and other priors in the case of a standard univariate Student t-distribution ⋮ Divergence measures and a general framework for local variational approximation ⋮ Variable selection for market basket analysis

Uses Software

• Fahrmeir

Cites Work

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• Bayesian analysis of dichotomous quantal response models
• Marginal Likelihood from the Gibbs Output
• Sampling-Based Approaches to Calculating Marginal Densities
• The Calculation of Posterior Distributions by Data Augmentation
• Bayes Factors
• Equation of State Calculations by Fast Computing Machines
• Bayesian Analysis of Binary and Polychotomous Response Data
• Monte Carlo sampling methods using Markov chains and their applications
• Multivariate statistical modelling based on generalized linear models.

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