Name
Title | ||
|---|---|---|
Mean field variational Bayesian inference for nonparametric regression with measurement error. |
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. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.csda.2013.07.014 | Computational Statistics & Data Analysis |
Keywords | Field | DocType |
measurement error setting,reasonable accuracy,methodological development,fast mean field variational,monte carlo method,nonparametric regression,mfvb method,classical measurement error,customized markov chain,mean field variational bayesian,markov chain monte carlo | Econometrics,Bayesian inference,Markov chain Monte Carlo,Nonparametric regression,Mean field theory,Statistics,Observational error,Mathematics,Bayes' theorem | Journal |
Volume | Issue | ISSN |
68 | C | 0167-9473 |
Citations | PageRank | References |
4 | 0.58 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tung H. Pham | 1 | 4 | 0.58 |
| John T. Ormerod | 2 | 10 | 4.78 |
| M. P. Wand | 3 | 51 | 10.35 |