Journal
REVISTA DE LA REAL ACADEMIA DE CIENCIAS EXACTAS FISICAS Y NATURALES SERIE A-MATEMATICAS
Volume 105, Issue 2, Pages 273-289Publisher
SPRINGER
DOI: 10.1007/s13398-011-0033-7
Keywords
Bayes factor; Intrinsic priors; Model comparison; Multivariate normal regression models; Objective Bayes procedures
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Funding
- Ministerio de Ciencia e Innovacion [MTM2008-05785, MTM2010-16087]
- Junta de Andalucia [SEJ-02814]
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In Moreno et al. (Rev R Acad Cien Ser A Mat 97:53-61, 2003) an objective Bayesian model comparison procedure for univariate normal regression models based on intrinsic priors was provided. However, in many applications the regression models entertained are multidimensional, and hence an extension of the procedure to this setting is required. This technical paper provides the intrinsic priors and their Bayes factors for testing multidimensional normal regression models. The sampling distributions of the sufficient statistic for model comparison are also found when sampling from both the null and the alternative models. This is a key tool for proving consistency of the model selection procedure based on the Bayes factor for intrinsic priors.
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