Search results for " Bayesian"

showing 10 items of 124 documents

Applications and Limitations of Robust Bayesian Bounds and Type II MLE

1994

Three applications of robust Bayesian analysis and three examples of its limitations are given. The applications that are reviewed are the development of an automatic Ockham’s Razor, outlier detection, and analysis of weighted distributions. Limitations of robust Bayesian bounds are highlighted through examples that include analysis of a paranormal experiment and a hierarchical model. This last example shows a disturbing difference between actual hierarchical Bayesian analysis and robust Bayesian bounds, a difference which also arises if, instead, a Type II MLE or empirical Bayes analysis is performed.

Computer sciencebusiness.industryBayesian probabilityMachine learningcomputer.software_genreHierarchical database modelStatistics::ComputationBayesian robustnessRobust Bayesian analysisPrior probabilityAnomaly detectionArtificial intelligenceBayes analysisbusinesscomputer
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Data Augmentation Approach in Bayesian Modelling of Presence-only Data

2011

Abstract Ecologists are interested in prediction of potential distribution of species in suitable areas, essential for planning conservation and management strategies. Unfortunately, often the only available information in such studies is the true presence of the species at few locations of the study area and the associated environmental covariates over the entire area, referred as presence-only data. We propose a Bayesian approach to estimate logistic linear regressions adapted to presence-only data through the introduction of a random approximation of the correction factor in the adjusted logistic model that allows us to overcome the need to know a priori the prevalence of the species.

Data augmentationPresence-only dataComputer scienceBayesian probabilityLogistic regressionBayesian inferencePseudo-absence approachBayesian statisticsBayesian model; Data augmentation; MCMC algorithm; Potential distribution; Presence-only data; Pseudo-absence approachBayesian model Data augmentation MCMC algorithm Presence-only data Pseudo-absence approach Potential distributionpotentialdistributionBayesian modelBayesian multivariate linear regressionPotential distributionStatisticsCovariateEconometricsGeneral Earth and Planetary Sciencespseudo-absence approach; potentialdistribution.; data augmentation; presence-only data; potential distribution; mcmc algorithm; bayesian modelBayesian linear regressionBayesian averageMCMC algorithmGeneral Environmental ScienceProcedia Environmental Sciences
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Spatio-temporal analysis of infectious diseases

2018

Los sistemas de vigilancia de salud pública colectan y analizan datos que soportan los programas de control y prevención de enfermedades en todo el mundo. En Colombia, el sistema de vigilancia en salud pública (SIVIGILA) esta encargado del flujo de datos e información de la vigilancia de las enfermedades de notificación obligatoria que afectan la salud de los Colombianos. Las enfermedades transmitidas por mosquitos tales como el dengue, la malaria, la fiebre amarilla, la enfermedad del virus del Chikungunya, la enfermedad del virus del Zika (EVZ) entre otras afectan seriamente la salud de las poblaciones a través de todo el país. Dentro de estas enfermedades se destacan la enfermedad del de…

DengueUNESCO::CIENCIAS DE LA TIERRA Y DEL ESPACIO::Geografía ::Geografía médica:CIENCIAS DE LA TIERRA Y DEL ESPACIO::Geografía ::Geografía médica [UNESCO]ZikaUNESCO::MATEMÁTICAS::Estadística ::Técnicas de predicción estadística:MATEMÁTICAS::Estadística ::Técnicas de inferencia estadística [UNESCO]:CIENCIAS DE LA VIDA::Biomatemáticas::Bioestadística [UNESCO]UNESCO::MATEMÁTICAS::Estadística ::Técnicas de inferencia estadísticaModelos jerárquicos Bayesianos:MATEMÁTICAS::Estadística ::Técnicas de predicción estadística [UNESCO]Mapeo de enfermedadesUNESCO::CIENCIAS DE LA VIDA::Biomatemáticas::Bioestadística
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Conditional Random Quantities and Iterated Conditioning in the Setting of Coherence

2013

We consider conditional random quantities (c.r.q.’s) in the setting of coherence. Given a numerical r.q. X and a non impossible event H, based on betting scheme we represent the c.r.q. X|H as the unconditional r.q. XH + μH c , where μ is the prevision assessed for X|H. We develop some elements for an algebra of c.r.q.’s, by giving a condition under which two c.r.q.’s X|H and Y|K coincide. We show that X|HK coincides with a suitable c.r.q. Y|K and we apply this representation to Bayesian updating of probabilities, by also deepening some aspects of Bayes’ formula. Then, we introduce a notion of iterated c.r.q. (X|H)|K, by analyzing its relationship with X|HK. Our notion of iterated conditiona…

Discrete mathematicsSettore MAT/06 - Probabilita' E Statistica MatematicaSettore INF/01 - Informaticaconditional random quantitiesCoherence (statistics)Bayesian inferencebayesian updatingcoherenceCombinatoricsconditional previsionsBayes' theoremIterated functionbayesian updating; conditional random quantities; betting scheme; conditional previsions; coherence; iterated conditioning; iterated conditioning.Coherence betting scheme conditional random quantities conditional previsions Bayesian updating iterated conditioning.Scheme (mathematics)iterated conditioningConditioningRepresentation (mathematics)betting schemeEvent (probability theory)Mathematics
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Comparison of different uncertainty techniques in urban stormwater quantity and quality modelling

2011

Abstract Urban drainage models are important tools used by both practitioners and scientists in the field of stormwater management. These models are often conceptual and usually require calibration using local datasets. The quantification of the uncertainty associated with the models is a must, although it is rarely practiced. The International Working Group on Data and Models, which works under the IWA/IAHR Joint Committee on Urban Drainage, has been working on the development of a framework for defining and assessing uncertainties in the field of urban drainage modelling. A part of that work is the assessment and comparison of different techniques generally used in the uncertainty assessm…

EngineeringEnvironmental Engineering* MCMCRainmedia_common.quotation_subjectBayesian probability* Parameter probability distributionBayesian inferencecomputer.software_genre* MICAsymbols.namesake* GLUEWater QualityStatistics* Bayesian inferenceComputer SimulationQuality (business)CitiesGLUEWaste Management and Disposal* Urban drainage modelWater Science and TechnologyCivil and Structural Engineeringmedia_common* SCEM-UALikelihood Functions* Multi-objective auto-calibrationSettore ICAR/03 - Ingegneria Sanitaria-Ambientalebusiness.industryEcological ModelingUncertaintyMarkov chain Monte CarloModels TheoreticalPollutionMarkov ChainsRunoff model* UncertaintieMetropolis–Hastings algorithmsymbolsProbability distribution* AMALGAMData miningbusinessMonte Carlo MethodcomputerAlgorithmsSoftware
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A predictive maintenance policy with imperfect monitoring

2010

For many systems,failure is a very dangerous or costly event. To reduce the occurrence of this event,it is necessary to implement a preventive maintenance policy to replace the critical elements before failure.Since elements do not often exhibit incipient faults, they are replaced before a complete exploiting of their useful life.To conjugate the objective of exploiting elements for almost all their useful life with the objective to avoid failure,condition based and,more recently,predictive maintenance policies have been proposed.This paper deals with this topic and proposes a procedure for the computation of the maintenance time that minimizes the global maintenance cost.By adopting a stoc…

Engineeringbusiness.industryStochastic modellingEvent (computing)Bayesian probabilityMonitoring systemSystem monitoringPreventive maintenanceIndustrial and Manufacturing EngineeringPredictive maintenanceReliability engineeringPredictive maintenance Bayesian Approach Imperfect maonitoringImperfectSafety Risk Reliability and QualitybusinessReliability Engineering & System Safety
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Modelling spatially sampled proportion processes​​

2018

Many ecological processes are measured as proportions and are spatially sampled. In all these cases the standard procedure has long been the transformation of proportional data with the arcsine square root or logit transformation, without considering the spatial correlation in any way. This paper presents a robust regression model to analyse this kind of data using a beta regression and including a spatially correlated term within the Bayesian framework. As a practical example, we apply the proposed approach to a spatio-temporally sampled fishery discard dataset.

Estadística bayesiana
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Editorial: Methodological issues in psychology and social sciences research

2023

In recent decades, the classical methods of studying the psychometric properties of tests have advanced to evolve into new innovative statistical methods, which allows obtaining a new view of the data. In this sense, progress has been made in the use of item response theory and in the use of structural equation models. Likewise, classical statistical inference methods have advanced in hypothesis testing and Bayesian statistics is rapidly making its way both in experimental studies and in psychometric studies. The aim of this issue has been to contribute to the dissemination of new research methodologies in quantitative and qualitative analysis in Psychology, as well as to evaluate the effec…

Estadística bayesianaPsicometriaGeneral PsychologyFrontiers in Psychology
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Differential analysis of indicators of achievement in objective tests

2003

Often objective tests to evaluate student qualifications are used. However, the selection between different evaluation criteria is in the hands of teachers or evaluators preferences. This investigation offers, briefly, a revision of some strategies utilized for objective evaluation. We also present other alternative strategies to the most classical ones. Afterwards, the strategies of evaluation have been analized with data from 114 subjects, who were evaluated with a test. The results suggest there are two kinds of strategies, one where only students' performance are evaluated, and other, where the test and the students are evaluated at the same time. We also show the fail of concordance be…

Evaluación del rendimiento pruebas objetivas estimación bayesiana análisis de items
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On the use of approximate Bayesian computation Markov chain Monte Carlo with inflated tolerance and post-correction

2020

Approximate Bayesian computation allows for inference of complicated probabilistic models with intractable likelihoods using model simulations. The Markov chain Monte Carlo implementation of approximate Bayesian computation is often sensitive to the tolerance parameter: low tolerance leads to poor mixing and large tolerance entails excess bias. We consider an approach using a relatively large tolerance for the Markov chain Monte Carlo sampler to ensure its sufficient mixing, and post-processing the output leading to estimators for a range of finer tolerances. We introduce an approximate confidence interval for the related post-corrected estimators, and propose an adaptive approximate Bayesi…

FOS: Computer and information sciences0301 basic medicineStatistics and Probabilitytolerance choiceGeneral MathematicsMarkovin ketjutInference01 natural sciencesStatistics - Computationapproximate Bayesian computation010104 statistics & probability03 medical and health sciencessymbols.namesakeMixing (mathematics)adaptive algorithmalgoritmit0101 mathematicsComputation (stat.CO)MathematicsAdaptive algorithmMarkov chainbayesilainen menetelmäApplied MathematicsProbabilistic logicEstimatorMarkov chain Monte CarloAgricultural and Biological Sciences (miscellaneous)Markov chain Monte CarloMonte Carlo -menetelmätimportance sampling030104 developmental biologyconfidence intervalsymbolsStatistics Probability and UncertaintyApproximate Bayesian computationGeneral Agricultural and Biological SciencesAlgorithm
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