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Mean field variational Bayesian inference for nonparametric regression with measurement error |
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| Affiliation: | 1. School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China;2. Department of Automation, Shanghai University, Shanghai 200444, China;3. Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China |
| Abstract: | 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. |
| Keywords: | Penalized splines Classical measurement error Markov chain Monte Carlo Variational approximations |
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