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...
Những tác giả chính: | Holmes, C, Held, L |
---|---|
Định dạng: | Journal article |
Ngôn ngữ: | English |
Được phát hành: |
2006
|
Những quyển sách tương tự
-
Bayesian Auxiliary Variable Models for Binary and Multinomial Regression
Bằng: Holmes, C, et al.
Được phát hành: (2006) -
Bayesian Estimation of the Multinomial Logit Model: A Comment on Holmes and Held, "Bayesian Auxiliary Variable Models for Binary and Multinomial Regression" Response
Bằng: Holmes, C, et al.
Được phát hành: (2011) -
Bayesian Lasso and multinomial logistic regression on GPU.
Bằng: Rok Češnovar, et al.
Được phát hành: (2017-01-01) -
MicroBVS: Dirichlet-tree multinomial regression models with Bayesian variable selection - an R package
Bằng: Matthew D. Koslovsky, et al.
Được phát hành: (2020-07-01) -
Taba Binary, Multinomial, and Ordinal Regression Models: New Machine Learning Methods for Classification
Bằng: Mohammad Tabatabai, et al.
Được phát hành: (2024-12-01)