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Bayesian nonparametric quantile regression using splines

Abstract:: A new technique based on Bayesian quantile regression that models the dependence of a quantile of one variable on the values of another using a natural cubic spline is presented. Inference is based on the posterior density of the spline and an associated smoothing parameter and is performed by means of a Markov chain Monte Carlo algorithm. Examples of the application of the new technique to two real environmental data sets and to simulated data for which polynomial modelling is inappropriate ...
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Publication status:: Published

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APA Style

Thompson, P., Cai, Y., Moyeed, R., Reeve, D., & Stander, J. (2010). Bayesian nonparametric quantile regression using splines. COMPUTATIONAL STATISTICS and DATA ANALYSIS, 54(4), 1138–1150.

MLA Style

Thompson, P., et al. “Bayesian Nonparametric Quantile Regression Using Splines.” COMPUTATIONAL STATISTICS and DATA ANALYSIS, vol. 54, no. 4, 2010, pp. 1138–50.

Chicago Style

Thompson, P, Y Cai, R Moyeed, D Reeve, and J Stander. 2010. “Bayesian Nonparametric Quantile Regression Using Splines.” COMPUTATIONAL STATISTICS and DATA ANALYSIS 54 (4): 1138–50.
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Publisher copy:: 10.1016/j.csda.2009.09.004

Authors

+ Thompson, P More by this author

Institution:

University of Oxford

Division:

MSD

Department:

Experimental Psychology

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Author

+ Cai, Y More by this author

Role:

Author

+ Moyeed, R More by this author

Role:

Author

+ Reeve, D More by this author

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Author

+ Stander, J More by this author

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Author

Bibliographic Details

Journal:: COMPUTATIONAL STATISTICS and DATA ANALYSIS
Volume:: 54
Issue:: 4
Pages:: 1138-1150
Publication date:: 2010-04-01
DOI:: 10.1016/j.csda.2009.09.004
ISSN:: 0167-9473

Item Description

Language:: English
Pubs id:: pubs:457549
UUID:: uuid:361b6add-04d4-4123-b2e6-66779e98971a
Local pid:: pubs:457549
Source identifiers:: 457549
Deposit date:: 2014-05-13

Terms of use

Copyright date:: 2010

Licence:: Terms and Conditions of Use for Oxford University Research Archive

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