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August 2000 Bayesian backfitting (with comments and a rejoinder by the authors
Trevor Hastie, Robert Tibshirani
Statist. Sci. 15(3): 196-223 (August 2000). DOI: 10.1214/ss/1009212815

Abstract

We propose general procedures for posterior sampling from additive and generalized additive models. The procedure is a stochastic generalization of the well-known backfitting algorithm for fitting additive models. One chooses a linear operator (“smoother”) for each predictor, and the algorithm requires only the application of the operator and its square root. The procedure is general and modular, and we describe its application to nonparametric, semiparametric and mixed models.

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Trevor Hastie. Robert Tibshirani. "Bayesian backfitting (with comments and a rejoinder by the authors." Statist. Sci. 15 (3) 196 - 223, August 2000. https://doi.org/10.1214/ss/1009212815

Information

Published: August 2000
First available in Project Euclid: 24 December 2001

zbMATH: 1059.62524
MathSciNet: MR1820768
Digital Object Identifier: 10.1214/ss/1009212815

Rights: Copyright © 2000 Institute of Mathematical Statistics

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Vol.15 • No. 3 • August 2000
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