Bayesian statistical decision theory.
Overview
| Works: | 274 works in 121 publications in 121 languages | |
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Titles
Bayesian analysis in statistics and econometrics :essays in honor of Arnold Zellner /
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Bayesian analysis in econometrics and statistics :the Zellner view and papers /
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Bayesian economics through numerical methods :a guide to econometrics and decision-making with prior information /
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Bayesian economics through numerical methods :a guide to econometrics and decision-making with prior information /
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Tools for statistical inference :methods for the exploration of posterior distributions and likelihood functions /
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The Bayesian choice :from decision-theoretic foundations to computational implementation /
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Markov chain Monte Carlo :stochastic simulation for Bayesian inference /
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Bayesian methods :an analysis for statisticians and interdisciplinary researchers /
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Subjective and objective Bayesian statistics :principles, models, and applications /
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Bayesian approaches to clinical trials and health care evaluation /
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Interpreting probability :controversies and developments in the early twentieth century /
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Measurement error and misclassification in statistics and epidemiology :impacts and Bayesian adjustments /
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Multivariate Bayesian statistics :models for source separation and signal unmixing /
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Applied Bayesian modeling and causal inference from incomplete-data perspectives :an essential journey with Donald Rubin's statistical family /
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Bayesian Networks and Influence Diagrams :A Guide to Construction and Analysis /
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Bayesian networks and influence diagrams :a guide to construction and analysis /
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Contemporary Bayesian and frequentist statistical research methods for natural resource scientists /
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Tools for constructing chronologies :crossing disciplinary boundaries /
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Bayesian nets and causality :philosophical and computational foundations /
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Markov chain Monte Carlo :stochastic simulation for Bayesian inference /
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Probabilistic methods for bioinformaticswith an introduction to Bayesian networks /
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Bayesian economics through numerical methodsa guide to econometrics and decision-making with prior information /
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Hierarchical modelling for the environmental sciences :statistical methods and applications /
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Frontiers of statistical decision making and Bayesian analysisin honor of James O. Berger /
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Missing data in longitudinal studies :strategies for Bayesian modeling and sensitivity analysis /
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Advanced mapping of environmental data :geostatistics, machine learning, and Bayesian maximum entropy /
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Frontiers of statistical decision making and Bayesian analysis :in honor of James O. Berger /
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Bayesian ideas and data analysis :an introduction for scientists and statisticians /
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Bayesian missing data problems :EM, data augmentation and noniterative computation /
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Financial risk management with Bayesian estimation of GARCH models :theory and applications /
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Large-scale inference :empirical Bayes methods for estimation, testing, and prediction /
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Missing data in longitudinal studiesstrategies for Bayesian modeling and sensitivity analysis /
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Bayesian missing data problemsEM, data augmentation and noniterative computation /
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Bayesian smoothing and regression for longitudinal, spatial and event history data
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Decision theory models for applications in artificial intelligenceconcepts and solutions /
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Essential Bayesian models :a derivative of Handbook of statistics : Bayesian thinking - modeling and computation, vol. 25 /
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Reasoning with probabilistic and deterministic graphical models :exact algorithms /
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Tackling the inverse problem for non-autonomous systemsapplication to the life sciences /
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Regularization and Bayesian methods for inverse problems in signal and image processing
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Bayesian methods for the physical scienceslearning from examples in astronomy and physics /
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Bayesian prediction and adaptive sampling algorithms for mobile sensor networksonline environmental field reconstruction in space and time /
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Bayesian data analysis in ecology using linear models withR, Bugs, and Stan
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Prior processes and their applicationsnonparametric bayesian estimation /
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Bayesian risk managementa guide to model risk and sequential learning in financial markets /
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The manual of strategic economic decision makingusing Bayesian belief networks to solve complex problems /
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Bayesian signal processingclassical, modern, and particle filtering methods /
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Maximizing information system availability through Bayesian belief network approachesemerging research and opportunities /
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Probabilistic finite element model updating using Bayesian statisticsapplications to aeronautical and mechanical engineering /
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Let the evidence speakusing bayesian thinking in law, medicine, ecology and other areas /
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The impact of economic freedom on state legitimacyan empirical investigation /
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Bayesian claims reserving methods in non-life insurance with Stanan introduction /
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Introduction to Bayesian estimation and copula models of dependence /
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Statistical rethinking :a Bayesian course with examples in R and Stan /
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Likelihood and Bayesian inferencewith applications in biology and medicine /
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Enhanced Bayesian network models for spatial time series predictionrecent research trend in data-driven predictive analytics /
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Bayesian networks for managing learner models in adaptive hypermedia systemsemerging research and opportunities /
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Case studies in applied Bayesian data scienceCIRM Jean-Morlet Chair, Fall 2018 /
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Applied hierarchical modeling in ecology.analysis of distribution, abundance and species richness in R and BUGS /Volume 1,Prelude and static models
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Nonparametric Bayesian learning for collaborative robot multimodal introspection
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Development of clinical decision support systems using Bayesian networkswith an example of a multi-disciplinary treatment decision for laryngeal cancer /
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Introduction to Bayesian methods in ecology and natural resources /
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Using R for Bayesian spatial and spatio-temporal health modeling /
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Likelihood and Bayesian inference :with applications in biology and medicine /
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Variational methods for machine learning with applications to deep networks
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Modelling spatial and spatial-temporal data :a Bayesian approach /
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Bayesian statistics for experimental scientists :a general introduction using distribution-free methods /
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Genomics data analysisfalse discovery rates and empirical Bayes methods /
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Test data engineeringlatent rank analysis, biclustering, and Bayesian network /
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Bayesian tensor decomposition for signal processing and machine learningmodeling, tuning-free algorithms, and applications /
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Bayesian real-time system identificationfrom centralized to distributed approach /
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Statistical modeling using Bayesian latent Gaussian modelswith applications in geophysics and environmental sciences /
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Bayesian nonparametric methods for missing data and causal inference /
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Bayesian multilevel models for repeated measures data :a conceptual and practical introduction in R /
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Bayesian filter design for computational medicinea state-space estimation framework /
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