Mean field variational Bayesian inference for nonparametric regression with measurement error

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.


Published in:
Computational Statistics & Data Analysis, 68, 375-387
Year:
2013
Publisher:
Amsterdam, Elsevier
ISSN:
0167-9473
Keywords:
Laboratories:


Note: The status of this file is: EPFL only


 Record created 2013-11-04, last modified 2018-03-17

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