On calibration of kullback-leibler divergence via prediction
In this paper we evaluate mean Kullback-Leibler divergence via predicting densities arising from various prediction methods applied to the multivariate single-sample normal model. We demonstrate that the degrees of freedom which index Geisser-Cornfield predictive densities are helpful in divergence...
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| Veröffentlicht in: | Communications in statistics. Theory and methods 1999-01, Vol.28 (1), p.67-85 |
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| container_title | Communications in statistics. Theory and methods |
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| creator | Keyes, Tim K. Levy, Martin S. |
| description | In this paper we evaluate mean Kullback-Leibler divergence via predicting densities arising from various prediction methods applied to the multivariate single-sample normal model. We demonstrate that the degrees of freedom which index Geisser-Cornfield predictive densities are helpful in divergence calibration. Alternative calibrations are derived based on sample size considerations. An application of each method to univariate prediction from the gamma model is provided. Comparisons are made with a probability-based calibration method. |
| doi_str_mv | 10.1080/03610929908832283 |
| format | Article |
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Theory and methods</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Keyes, Tim K.</au><au>Levy, Martin S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>On calibration of kullback-leibler divergence via prediction</atitle><jtitle>Communications in statistics. Theory and methods</jtitle><date>1999-01-01</date><risdate>1999</risdate><volume>28</volume><issue>1</issue><spage>67</spage><epage>85</epage><pages>67-85</pages><issn>0361-0926</issn><eissn>1532-415X</eissn><coden>CSTMDC</coden><abstract>In this paper we evaluate mean Kullback-Leibler divergence via predicting densities arising from various prediction methods applied to the multivariate single-sample normal model. We demonstrate that the degrees of freedom which index Geisser-Cornfield predictive densities are helpful in divergence calibration. Alternative calibrations are derived based on sample size considerations. 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| issn | 0361-0926 1532-415X |
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| source | Access via Taylor & Francis |
| subjects | Bayesian Distribution theory estimative Exact sciences and technology linear models Mathematics Nonparametric inference predicting densities Probability and statistics Sciences and techniques of general use Statistics Sufficiency and information |
| title | On calibration of kullback-leibler divergence via prediction |
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