Search results for "Reference Analysis"

showing 2 items of 2 documents

Objective Bayesian point and region estimation in location-scale models.

2007

Point and region estimation may both be described as specific decision problems. In point estimation, the action space is the set of possible values of the quantity on interest; in region estimation, the action space is the set of its possible credible regions. Foundations dictate that the solution to these decision problems must depend on both the utility function and the prior distribution. Estimators intended for general use should surely be invariant under one-to-one transformations, and this requires the use of an invariant loss function; moreover, an objective solution requires the use of a prior which does not introduce subjective elements. The combined use of an invariant informatio…

Intrinsic LossTeoria de la decisióRegion Estimation:62 Statistics::62B Sufficiency and information [Classificació AMS]Intrinsic DiscrepancyStatisticsEstadísticaReference Analysis:MATEMÁTICAS::Estadística [UNESCO]UNESCO::MATEMÁTICAS::EstadísticaCredible RegionsConfidence Intervals ; Credible Regions ; Decision Theory ; Intrinsic Discrepancy ; Intrinsic Loss ; Location-Scale Models ; Noninformative Prior ; Reference Analysis ; Region Estimation ; Point EstimationPoint EstimationDecision TheoryInferenceInferència:62 Statistics::62F Parametric inference [Classificació AMS]Confidence IntervalsLocation-Scale ModelsNoninformative Prior:62 Statistics::62C Decision theory [Classificació AMS]
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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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