Use of the Gibbs Sampler to Obtain Conditional Tests, with Applications
A random sample is drawn from a distribution which admits a minimal sufficient statistic for the parameters. The Gibbs sampler is proposed to generate samples, called conditionally sufficient or co-sufficient samples, from the conditional distribution of the sample given its value of the sufficient...
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| Veröffentlicht in: | Biometrika 2007-12, Vol.94 (4), p.992-998 |
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| container_end_page | 998 |
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| container_title | Biometrika |
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| creator | Lockhart, Richard A. O'Reilly, Federico J. Stephens, Michael A. |
| description | A random sample is drawn from a distribution which admits a minimal sufficient statistic for the parameters. The Gibbs sampler is proposed to generate samples, called conditionally sufficient or co-sufficient samples, from the conditional distribution of the sample given its value of the sufficient statistic. The procedure is illustrated for the gamma distribution. Co-sufficient samples may be used to give exact tests of fit; for the gamma distribution these are compared for size and power with approximate tests based on the parametric bootstrap. |
| doi_str_mv | 10.1093/biomet/asm065 |
| format | Article |
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| ispartof | Biometrika, 2007-12, Vol.94 (4), p.992-998 |
| issn | 0006-3444 1464-3510 |
| language | eng |
| recordid | cdi_proquest_journals_201695697 |
| source | RePEc; JSTOR Mathematics & Statistics; JSTOR Archive Collection A-Z Listing; Oxford University Press Journals All Titles (1996-Current) |
| subjects | Actuarial science Applications Biology, psychology, social sciences Bootstrap method Comparative studies Distribution theory Empirical distribution function test Estimation methods Exact sciences and technology Gaussian distributions General topics Goodness-of-fit test Markov analysis Markov chains Mathematics Miscellanea Normal distribution P values Parametric bootstrap Probability and statistics Probability theory and stochastic processes Random sampling Rao–Blackwell Sampling distributions Sciences and techniques of general use Statistics Sufficiency and information Sufficient statistic |
| title | Use of the Gibbs Sampler to Obtain Conditional Tests, with Applications |
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