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Non-Standard Semiparametric Regression via BRugs

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  • Jennifer K. Marley
  • Matthew P. Wand
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    Abstract

    We provide several illustrations of Bayesian semiparametric regression analyses in the BRugs package. BRugs facilitates use of the BUGS inference engine from the R computing environment and allows analyses to be managed using scripts. The examples are chosen to represent an array of non-standard situations, for which mixed model software is not viable. The situations include: the response variable being outside of the one-parameter exponential family, data subject to missingness, data subject to measurement error and parameters entering the model via an index.

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    Bibliographic Info

    Article provided by American Statistical Association in its journal Journal of Statistical Software.

    Volume (Year): 37 ()
    Issue (Month): i05 ()
    Pages:

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    Handle: RePEc:jss:jstsof:37:i05

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    Web page: http://www.jstatsoft.org/

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    Cited by:
    1. Donald, Margaret & Alston, Clair L. & Young, Rick R. & Mengersen, Kerrie L., 2011. "A Bayesian analysis of an agricultural field trial with three spatial dimensions," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3320-3332, December.
    2. Chiara Bocci & Emilia Rocco, 2014. "Estimates for geographical domains through geoadditive models in presence of incomplete geographical information," Statistical Methods and Applications, Springer, vol. 23(2), pages 283-305, June.

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