0000000000680619

AUTHOR

Dongchu Sun

showing 4 related works from this author

Objective Priors for Discrete Parameter Spaces

2012

This article considers the development of objective prior distributions for discrete parameter spaces. Formal approaches to such development—such as the reference prior approach—often result in a constant prior for a discrete parameter, which is questionable for problems that exhibit certain types of structure. To take advantage of structure, this article proposes embedding the original problem in a continuous problem that preserves the structure, and then using standard reference prior theory to determine the appropriate objective prior. Four different possibilities for this embedding are explored, and applied to a population-size model, the hypergeometric distribution, the multivariate hy…

Statistics and ProbabilityMathematical optimizationNegative hypergeometric distributionGeometric distributionHypergeometric distributionDirichlet distributionBinomial distributionsymbols.namesakeBeta-binomial distributionPrior probabilitysymbolsStatistics Probability and UncertaintyCompound probability distributionMathematicsJournal of the American Statistical Association
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Rejoinder on: Natural Induction: An Objective Bayesian Approach

2009

Giron and Moreno. We certainly agree with Professors Giron and Moreno on the interest in sensitivity of any Bayesian result to changes in the prior. That said, we also consider of considerable pragmatic importance to be able to single out a unique, particular prior which may reasonably be proposed as the reference prior for the problem under study, in the sense that the corresponding posterior of the quantity of interest could be routinely used in practice when no useful prior information is available or acceptable. This is precisely what we have tried to do for the twin problems of the rule of succession and the law of natural induction. The discussants consider the limiting binomial versi…

Algebra and Number TheoryRule of successionApplied MathematicsBayesian probabilityComputational MathematicsPrior probabilityNatural (music)Geometry and TopologySensitivity (control systems)Problem of inductionNull hypothesisMathematical economicsAnalysisMathematicsStatistical hypothesis testing
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Overall Objective Priors

2015

In multi-parameter models, reference priors typically depend on the parameter or quantity of interest, and it is well known that this is necessary to produce objective posterior distributions with optimal properties. There are, however, many situations where one is simultaneously interested in all the parameters of the model or, more realistically, in functions of them that include aspects such as prediction, and it would then be useful to have a single objective prior that could safely be used to produce reasonable posterior inferences for all the quantities of interest. In this paper, we consider three methods for selecting a single objective prior and study, in a variety of problems incl…

Statistics and ProbabilityComputer sciencebusiness.industryApplied MathematicsMathematics - Statistics TheoryStatistics Theory (math.ST)Joint Reference PriorReference AnalysisMachine learningcomputer.software_genreLogarithmic DivergenceObjective PriorsVariety (cybernetics)Single objectiveMultinomial ModelPrior probabilityFOS: MathematicsMultinomial distributionMultinomial modelArtificial intelligencebusinesscomputerReference analysisBayesian Analysis
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Natural induction: An objective bayesian approach

2009

The statistical analysis of a sample taken from a finite population is a classic problem for which no generally accepted objective Bayesian results seem to exist. Bayesian solutions to this problem may be very sensitive to the choice of the prior, and there is no consensus as to the appropriate prior to use.

education.field_of_studyAlgebra and Number Theorybusiness.industryApplied MathematicsBayesian probabilityPopulationBayes factorSample (statistics)Machine learningcomputer.software_genreBinomial distributionBayesian statisticsComputational MathematicsEconometricsBayesian hierarchical modelingGeometry and TopologyArtificial intelligencebusinesseducationcomputerAnalysisJeffreys priorMathematicsRevista de la Real Academia de Ciencias Exactas, Fisicas y Naturales. Serie A. Matematicas
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