Search results for "informative prior"

showing 4 items of 4 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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Can bayesian models play a role in dental caries epidemiology? Evidence from an application to the BELCAP data set

2012

Objectives The aim of this study was to show the potential of Bayesian analysis in statistical modelling of dental caries data. Because of the bounded nature of the dmft (DMFT) index, zero-inflated binomial (ZIB) and beta-binomial (ZIBB) models were considered. The effects of incorporating prior information available about the parameters of models were also shown. Methods The data set used in this study was the Belo Horizonte Caries Prevention (BELCAP) study (Bohning et al. (1999)), consisting of five variables collected among 797 Brazilian school children designed to evaluate four programmes for reducing caries. Only the eight primary molar teeth were considered in the data set. A data aug…

Malebounded dataBest fittingBayesian probabilityDeviance (statistics)informative priorDental CariesSettore MED/42 - Igiene Generale E ApplicataSettore MED/01 - Statistica MedicaOverdispersionPrior probabilityStatisticsHumansMedicineChildGeneral DentistryBayesian analysidmftDMF Indexbusiness.industryBelo Horizonte Caries Preventionzero-inflated betabinomialCaries epidemiologyPublic Health Environmental and Occupational HealthBayes TheoremStatistical modelRegressionzero-inflated binomialFemalebusinessAlgorithmsBrazilBayesian analysis; Belo Horizonte Caries Prevention; bounded data; dmft; informative prior; zero-inflated betabinomial; zero-inflated binomialCommunity Dentistry and Oral Epidemiology
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A Bayesian stable isotope mixing model for coping with multiple isotopes, multiple trophic steps and small sample sizes

2022

We introduce a Bayesian stable isotope mixing model for estimating the relative contributions of different dietary components to the tissues of consumers within food webs. The model is implemented with the probabilistic programming language Stan. The model incorporates isotopes of multiple elements (e.g. C, N, H) for two trophic levels, when the structure of the food web is known. In addition, the model allows inclusion of latent trophic levels (i.e. for which no empirical data are available) intermediate between sources and measured consumers. Running the model in simulations driven by a real dataset from Finnish lakes, we tested the sensitivity of the posterior distributions by altering c…

isotoopitEcological Modelingbayesilainen menetelmästable isotopeBayesian mixing modelinformative priormultiple levelsEcology Evolution Behavior and Systematicsravintoverkot
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Bayesian analysis of a disability model for lung cancer survival

2016

Bayesian reasoning, survival analysis and multi-state models are used to assess survival times for Stage IV non-small-cell lung cancer patients and the evolution of the disease over time. Bayesian estimation is done using minimum informative priors for the Weibull regression survival model, leading to an automatic inferential procedure. Markov chain Monte Carlo methods have been used for approximating posterior distributions and the Bayesian information criterion has been considered for covariate selection. In particular, the posterior distribution of the transition probabilities, resulting from the multi-state model, constitutes a very interesting tool which could be useful to help oncolog…

Statistics and ProbabilityLung NeoplasmsEpidemiologyComputer scienceMatemáticasPosterior probabilityBayesian probabilityEstadísticaBiostatisticsAccelerated failure time modelsBayesian inference01 natural sciences010104 statistics & probability03 medical and health sciencesBayes' theoremsymbols.namesake0302 clinical medicineHealth Information ManagementBayesian information criterionCarcinoma Non-Small-Cell LungStatisticsPrior probabilityHumans0101 mathematicsBiología y BiomedicinaNeoplasm StagingInformáticaBayes estimatorBayes TheoremMarkov chain Monte CarloSurvival AnalysisBayesian information criterionMarkov Chains030220 oncology & carcinogenesisMinimum informative priorsymbolsMulti-state modelsRegression AnalysisWeibull distributionMonte Carlo Method
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