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Article: Statistical inference for truncated Dirichlet distribution and its application in misclassification
Title | Statistical inference for truncated Dirichlet distribution and its application in misclassification |
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Authors | |
Keywords | Bayesian Inference Conditional Distribution Method Constrained Mle Experimental Design Gibbs Sampler Screening Test Sensitivity Specificity |
Issue Date | 2000 |
Publisher | Wiley - V C H Verlag GmbH & Co KGaA. The Journal's web site is located at http://www.interscience.wiley.com/biometricaljournal |
Citation | Biometrical Journal, 2000, v. 42 n. 8, p. 1053-1068 How to Cite? |
Abstract | This paper is concerned with the statistical inference of a truncated Dirichlet distribution (TDD) arising in the general context of misclassified multinomial models (such as medical screening or diagnostic tests) and experimental design with mixtures. By employing the conditional distribution method, we offer a generating procedure for the TDD. Alternatively, a sampling-based approach using the Gibbs sampler was provided as a means for developing the posterior moments of interest. Finding the mode of a TDD is equivalent to extracting the constrained maximum likelihood estimate (MLE) of parameter vector in a multinomial model. Based upon a theoretic result, we propose an algorithm to calculate the constrained MLE. Applications in misclassification are presented. |
Persistent Identifier | http://hdl.handle.net/10722/172385 |
ISSN | 2021 Impact Factor: 1.715 2020 SCImago Journal Rankings: 1.108 |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Fang, KT | en_US |
dc.contributor.author | Geng, Z | en_US |
dc.contributor.author | Tian, GL | en_US |
dc.date.accessioned | 2012-10-30T06:22:16Z | - |
dc.date.available | 2012-10-30T06:22:16Z | - |
dc.date.issued | 2000 | en_US |
dc.identifier.citation | Biometrical Journal, 2000, v. 42 n. 8, p. 1053-1068 | en_US |
dc.identifier.issn | 0323-3847 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/172385 | - |
dc.description.abstract | This paper is concerned with the statistical inference of a truncated Dirichlet distribution (TDD) arising in the general context of misclassified multinomial models (such as medical screening or diagnostic tests) and experimental design with mixtures. By employing the conditional distribution method, we offer a generating procedure for the TDD. Alternatively, a sampling-based approach using the Gibbs sampler was provided as a means for developing the posterior moments of interest. Finding the mode of a TDD is equivalent to extracting the constrained maximum likelihood estimate (MLE) of parameter vector in a multinomial model. Based upon a theoretic result, we propose an algorithm to calculate the constrained MLE. Applications in misclassification are presented. | en_US |
dc.language | eng | en_US |
dc.publisher | Wiley - V C H Verlag GmbH & Co KGaA. The Journal's web site is located at http://www.interscience.wiley.com/biometricaljournal | en_US |
dc.relation.ispartof | Biometrical Journal | en_US |
dc.subject | Bayesian Inference | en_US |
dc.subject | Conditional Distribution Method | en_US |
dc.subject | Constrained Mle | en_US |
dc.subject | Experimental Design | en_US |
dc.subject | Gibbs Sampler | en_US |
dc.subject | Screening Test | en_US |
dc.subject | Sensitivity | en_US |
dc.subject | Specificity | en_US |
dc.title | Statistical inference for truncated Dirichlet distribution and its application in misclassification | en_US |
dc.type | Article | en_US |
dc.identifier.email | Tian, GL: gltian@hku.hk | en_US |
dc.identifier.authority | Tian, GL=rp00789 | en_US |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.scopus | eid_2-s2.0-0034551876 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-0034551876&selection=ref&src=s&origin=recordpage | en_US |
dc.identifier.volume | 42 | en_US |
dc.identifier.issue | 8 | en_US |
dc.identifier.spage | 1053 | en_US |
dc.identifier.epage | 1068 | en_US |
dc.publisher.place | Germany | en_US |
dc.identifier.scopusauthorid | Fang, KT=7102880697 | en_US |
dc.identifier.scopusauthorid | Geng, Z=7101959672 | en_US |
dc.identifier.scopusauthorid | Tian, GL=25621549400 | en_US |
dc.identifier.issnl | 0323-3847 | - |