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Abstract Details
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Activity Number:
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74
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Type:
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Contributed
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Date/Time:
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Sunday, July 31, 2011 : 4:00 PM to 5:50 PM
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Sponsor:
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Section on Bayesian Statistical Science
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| Abstract - #301836 |
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Title:
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Bayes Factors in a Smoothing Spline ANOVA Model
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Author(s):
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Chin-I Cheng*+ and Paul Speckman
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Companies:
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Central Michigan University and University of Missouri at Columbia
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Address:
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110 Pearce Hall, Mt Pleasant, MI, 48859,
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Keywords:
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smoothing spline ANOVA ;
reproducing kernel ;
scaled chi-squared prior ;
Bridge sampling
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Abstract:
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Smoothing spline ANOVA extends traditional ANOVA modeling to models that include nonparametric function estimates. We introduce suitable priors for computing Bayes factors to test all of the elements in the model. The priors selected for hypothesis testing may be different from those for estimation. We can also use the Bayes factors for variable selection. Bridge sampling and Monte Carlo integration are adapted to facilitate the computation. The methods are illustrated using a real dataset from an experiment measuring potassium in dogs.
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