Please use this identifier to cite or link to this item: https://doi.org/10.1080/00949650601141712
DC FieldValue
dc.titleOn the multivariate predictive distribution of multi-dimensional effective dose: A Bayesian approach
dc.contributor.authorLi, J.
dc.contributor.authorZhang, C.
dc.contributor.authorNordheim, E.V.
dc.contributor.authorLehner, C.E.
dc.date.accessioned2014-10-28T05:14:02Z
dc.date.available2014-10-28T05:14:02Z
dc.date.issued2008
dc.identifier.citationLi, J., Zhang, C., Nordheim, E.V., Lehner, C.E. (2008). On the multivariate predictive distribution of multi-dimensional effective dose: A Bayesian approach. Journal of Statistical Computation and Simulation 78 (5) : 429-442. ScholarBank@NUS Repository. https://doi.org/10.1080/00949650601141712
dc.identifier.issn00949655
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/105279
dc.description.abstractWe propose a Bayesian procedure to sample from the distribution of the multi-dimensional effective dose. This effective dose is the set of dose levels of multiple predictive factors that produce a binary response with a fixed probability.We apply our algorithms to parametric and semiparametric logistics regression models, respectively. The graphical display of random samples obtained through Markov chain Monte Carlo can provide some insight into the predictive distribution. © 2008 Taylor & Francis.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1080/00949650601141712
dc.sourceScopus
dc.subjectMulti-dimensional effective dose
dc.subjectMultivariate joint distribution
dc.subjectPosterior distribution
dc.subjectSimulating conditional distribution
dc.typeArticle
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.doi10.1080/00949650601141712
dc.description.sourcetitleJournal of Statistical Computation and Simulation
dc.description.volume78
dc.description.issue5
dc.description.page429-442
dc.identifier.isiut000257291200004
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