Mean field variational Bayesian inference for nonparametric regression with measurement error

被引：15

作者：

Pham, Tung H. ^{[1
]}

Ormerod, John T. ^{[2
]}

Wand, M. P. ^{[3
]}

机构：

[1] Ecole Polytech Fed Lausanne, Inst Math, Stn 8, CH-1015 Lausanne, Switzerland

[2] Univ Sydney, Sch Math & Stat, Sydney, NSW 2006, Australia

[3] Univ Technol Sydney, Sch Math Sci, Broadway, NSW 2007, Australia

来源：

COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2013年 / 68卷

基金：

澳大利亚研究理事会;

关键词：

Penalized splines; Classical measurement error; Markov chain Monte Carlo; Variational approximations; SEMIPARAMETRIC REGRESSION; MODELS;

D O I：

10.1016/j.csda.2013.07.014

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A fast mean field variational Bayes (MFVB) approach to nonparametric regression when the predictors are subject to classical measurement error is investigated. It is shown that the use of such technology to the measurement error setting achieves reasonable accuracy. In tandem with the methodological development, a customized Markov chain Monte Carlo method is developed to facilitate the evaluation of accuracy of the MFVB method. Crown Copyright (C) 2013 Published by Elsevier B.V. All rights reserved.

引用

页码：375 / 387

页数：13

共 19 条

[1]

[Anonymous], 2006, Pattern recognition and machine learning

[2] Bayesian smoothing and regression splines for measurement error problems [J].

Berry, SM ;

Carroll, RJ ;

Ruppert, D .

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2002, 97 (457) :160-169

[3]

Bralower TJ, 1997, GEOL SOC AM BULL, V109, P1421, DOI 10.1130/0016-7606(1997)109<1421:MCSISO>2.3.CO

[4]

[5]

Carroll R.J., 2004, Journal of the American Statistical Association, V99, P661

[6]

Carroll R. J., 2006, MEASUREMENT ERROR NO

[7] Non-parametric regression estimation from data contaminated by a mixture of Berkson and classical errors [J].

Carroll, Raymond J. ;

Delaigle, Aurore ;

Hall, Peter .

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2007, 69 :859-878

[8] SiZer for exploration of structures in curves [J].

Chaudhuri, P ;

Marron, JS .

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1999, 94 (447) :807-823

[9] Variational Bayesian Inference for Parametric and Nonparametric Regression With Missing Data [J].

Faes, C. ;

Ormerod, J. T. ;

Wand, M. P. .

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2011, 106 (495) :959-971

[10] Additive models with predictors subject to measurement error [J].

Ganguli, B ;

Staudenmayer, J ;

Wand, MP .

AUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, 2005, 47 (02) :193-202

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