Search results for "Bayesian [statistical analysis]"

showing 10 items of 299 documents

Bayesian analysis of a Gibbs hard-core point pattern model with varying repulsion range

2014

A Bayesian solution is suggested for the modelling of spatial point patterns with inhomogeneous hard-core radius using Gaussian processes in the regularization. The key observation is that a straightforward use of the finite Gibbs hard-core process likelihood together with a log-Gaussian random field prior does not work without penalisation towards high local packing density. Instead, a nearest neighbour Gibbs process likelihood is used. This approach to hard-core inhomogeneity is an alternative to the transformation inhomogeneous hard-core modelling. The computations are based on recent Markovian approximation results for Gaussian fields. As an application, data on the nest locations of Sa…

Statistics and ProbabilityMathematical optimizationGaussianBayesian probabilityBayesian analysisMarkov processRegularization (mathematics)symbols.namesakeGaussian process regularisationPERFECT SIMULATIONRange (statistics)Statistical physicsGaussian processMathematicsta113ta112Random fieldApplied MathematicsInhomogeneousSand Martin's nestsTRANSFORMATIONHard-core point processComputational MathematicsTransformation (function)Computational Theory and MathematicssymbolsINFERENCECOMPUTATIONAL STATISTICS AND DATA ANALYSIS
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Bayesian Smoothing in the Estimation of the Pair Potential Function of Gibbs Point Processes

1999

A flexible Bayesian method is suggested for the pair potential estimation with a high-dimensional parameter space. The method is based on a Bayesian smoothing technique, commonly applied in statistical image analysis. For the calculation of the posterior mode estimator a new Monte Carlo algorithm is developed. The method is illustrated through examples with both real and simulated data, and its extension into truly nonparametric pair potential estimation is discussed.

Statistics and ProbabilityMathematical optimizationposterior mode estimatorMarkov chain Monte Carlo methodsMonte Carlo methodBayesian probabilityRejection samplingEstimatorMarkov chain Monte CarloBayesian smoothingGibbs processesHybrid Monte Carlosymbols.namesakeMarquardt algorithmsymbolspair potential functionPair potentialAlgorithmMathematicsGibbs samplingBernoulli
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Gaussian component mixtures and CAR models in Bayesian disease mapping

2012

Hierarchical Bayesian models involving conditional autoregression (CAR) components are commonly used in disease mapping. An alternative model to the proper or improper CAR is the Gaussian component mixture (GCM) model. A review of CAR and GCM models is provided in univariate settings where only one disease is considered, and also in multivariate situations where in addition to the spatial dependence between regions, the dependence among multiple diseases is analyzed. A performance comparison between models using a set of simulated data to help illustrate their respective properties is reported. The results show that both in univariate and multivariate settings, both models perform in a comp…

Statistics and ProbabilityMultivariate statisticsApplied MathematicsGaussianBayesian probabilityUnivariateVariable-order Bayesian networkComputational Mathematicssymbols.namesakeComputational Theory and MathematicsAutoregressive modelStatisticsRange (statistics)symbolsEconometricsSpatial dependenceMathematicsComputational Statistics & Data Analysis
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Analisis bayesiano de los contrastes de hipotesis parametricos

1985

Classical solutions to parametric hypothesis testing are shown to be particular instances of the Bayesian solution to a decision problem with two alternatives, in which the increase in utility for rejecting a false null is a linear function of the discrepancy between the accepted parametric model and the more likely model under the null.

Statistics and ProbabilityNull (mathematics)Parametric modelStatistics Probability and UncertaintyDecision problemAlgorithmBayesian solutionLinear functionParametric statisticsMathematicsStatistical hypothesis testingTrabajos de Estadistica Y de Investigacion Operativa
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Frequentist and Bayesian approaches for a joint model for prostate cancer risk and longitudinal prostate-specific antigen data

2015

The paper describes the use of frequentist and Bayesian shared-parameter joint models of longitudinal measurements of prostate-specific antigen (PSA) and the risk of prostate cancer (PCa). The motivating dataset corresponds to the screening arm of the Spanish branch of the European Randomized Screening for Prostate Cancer study. The results show that PSA is highly associated with the risk of being diagnosed with PCa and that there is an age-varying effect of PSA on PCa risk. Both the frequentist and Bayesian paradigms produced very close parameter estimates and subsequent 95% confidence and credibility intervals. Dynamic estimations of disease-free probabilities obtained using Bayesian infe…

Statistics and ProbabilityPREDICTIONBayesian probabilityurologic and male genital diseasesBayesian inferenceGeneralized linear mixed modelPSAProstate cancerLATENT CLASS MODELSAnàlisi de supervivència (Biometria)Frequentist inference62N01Statisticsprostate cancer screeningSurvival analysis (Biometry)FAILUREMedicineProstate cancer riskTO-EVENT DATAbusiness.industryjoint modelsMORTALITYDISEASE PROGRESSIONmedicine.diseaselinear mixed modelsTIMEProstate-specific antigenProstate cancer screeningshared-parameter models:Matemàtiques i estadística::Estadística matemàtica [Àrees temàtiques de la UPC]62P10SURVIVALStatistics Probability and Uncertaintyrelative risk modelsFOLLOW-UPbusinessJournal of Applied Statistics
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Analysis of the renal transplant waiting list in the País Valencià (Spain).

2005

In this paper we analyse the renal transplant waiting list of the Pais Valencia in Spain, using Queueing theory. The customers of this queue are patients with end-stage renal failure waiting for a kidney transplant. We set up a simplified model to represent the flow of the customers through the system, and perform Bayesian inference to estimate parameters in the model. Finally, we consider several scenarios by tuning the estimations achieved and computationally simulate the behaviour of the queue under each one. The results indicate that the system could reach equilibrium at some point in the future and the model forecasts a slow decrease in the size of the waiting list in the short and mid…

Statistics and ProbabilityQueueing theoryOperations researchWaiting ListsEpidemiologyComputer scienceSystems TheoryBayes TheoremBayesian inferenceKidney transplantKidney TransplantationSet (abstract data type)Bayesian statisticsWaiting listRenal transplantSpainHumansQueueStatistics in medicine
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Distribucion final de referencia para el problema de Fieller-Creasy

1982

The problem of making inferences about the ratio of two normal populations is usually known as the Fieller-Creasy problem, and it gave rise to a controversy among fiducialists and confidence-intervalists. A Bayesian solution to such a problem when the two normal populations have the same unknown variance was presented by Bernardo (1977) using reference non-informative prior distributions. The solution to the case in which the variances are not assumed equal is obtained here. Some numerical results for artificial populations are given

Statistics and ProbabilityStatisticsCalculusVariance (accounting)Statistics Probability and UncertaintyBayesian solutionMathematicsTrabajos de Estadistica y de Investigacion Operativa
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Reference Posterior Distributions for Bayesian Inference

1979

Statistics and Probabilitybusiness.industry010102 general mathematicsBayes factorPattern recognitionBayesian inference01 natural sciencesBayesian statistics010104 statistics & probabilityFrequentist inferenceFiducial inferenceStatistical inferenceBayesian experimental designArtificial intelligence0101 mathematicsBayesian linear regressionbusinessMathematicsJournal of the Royal Statistical Society: Series B (Methodological)
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On implementation of the Gibbs sampler for estimating the accuracy of multiple diagnostic tests

2010

Implementation of the Gibbs sampler for estimating the accuracy of multiple binary diagnostic tests in one population has been investigated. This method, proposed by Joseph, Gyorkos and Coupal, makes use of a Bayesian approach and is used in the absence of a gold standard to estimate the prevalence, the sensitivity and specificity of medical diagnostic tests. The expressions that allow this method to be implemented for an arbitrary number of tests are given. By using the convergence diagnostics procedure of Raftery and Lewis, the relation between the number of iterations of Gibbs sampling and the precision of the estimated quantiles of the posterior distributions is derived. An example conc…

Statistics and Probabilityeducation.field_of_studygastroesophageal reflux diseaseBayesian probabilityPopulationGold standard (test)Settore FIS/03 - Fisica Della MateriaGibbs sampler; Bayesian analysis; convergence diagnostics; diagnostic tests; gastroesophageal reflux diseaseSettore MED/01 - Statistica MedicaData setsymbols.namesakediagnostic testGibbs samplerConvergence (routing)Statisticsconvergence diagnosticsymbolsSensitivity (control systems)Statistics Probability and UncertaintyeducationAlgorithmBayesian analysiQuantileMathematicsGibbs samplingJournal of Applied Statistics
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Contributed discussion on article by Pratola

2016

The author should be commended for his outstanding contribution to the literature on Bayesian regression tree models. The author introduces three innovative sampling approaches which allow for efficient traversal of the model space. In this response, we add a fourth alternative.

Statistics and Probabilitymodel selectionMarkov Chain Monte Carlo (MCMC)Bayesian regression treeComputer scienceBig dataBayesian regression tree (BRT) modelsComputingMilieux_LEGALASPECTSOFCOMPUTINGbirth–death processMachine learningcomputer.software_genreSequential Monte Carlo methods01 natural sciencespopulation Markov chain Monte Carlo010104 statistics & probabilitysymbols.namesakebig data0502 economics and businessBayesian Regression Trees (BART)0101 mathematics050205 econometrics Bayesian treed regressionMultiple Try Metropolis algorithmsINFERÊNCIA ESTATÍSTICAbusiness.industryApplied MathematicsModel selection05 social sciencesRejection samplingData scienceVariable-order Bayesian networkTree (data structure)Tree traversalMarkov chain Monte Carlocontinuous time Markov processsymbolsArtificial intelligencebusinessBayesian linear regressioncommunication-freecomputerGibbs samplingBayesian Analysis
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