Bayesian auxiliary variable models for binary and multinomial regression
In this paper we discuss auxiliary variable approaches to Bayesian binary and multinomial regression. These approaches are ideally suited to automated Markov chain Monte Carlo simulation. In the first part we describe a simple technique using joint updating that improves the performance of the conve...
المؤلفون الرئيسيون: | Holmes, C, Held, L |
---|---|
التنسيق: | Journal article |
اللغة: | English |
منشور في: |
2006
|
مواد مشابهة
-
Bayesian Auxiliary Variable Models for Binary and Multinomial Regression
حسب: Holmes, C, وآخرون
منشور في: (2006) -
Bayesian Estimation of the Multinomial Logit Model: A Comment on Holmes and Held, "Bayesian Auxiliary Variable Models for Binary and Multinomial Regression" Response
حسب: Holmes, C, وآخرون
منشور في: (2011) -
Bayesian Lasso and multinomial logistic regression on GPU.
حسب: Rok Češnovar, وآخرون
منشور في: (2017-01-01) -
MicroBVS: Dirichlet-tree multinomial regression models with Bayesian variable selection - an R package
حسب: Matthew D. Koslovsky, وآخرون
منشور في: (2020-07-01) -
Taba Binary, Multinomial, and Ordinal Regression Models: New Machine Learning Methods for Classification
حسب: Mohammad Tabatabai, وآخرون
منشور في: (2024-12-01)