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Bayesian inference / Javier Prieto Tejedor (2017)  

Public Titre : Bayesian inference Type de document : Monographie Auteurs : Javier Prieto Tejedor, Éditeur scientifique Editeur : London [UK] : IntechOpen Année de publication : 2017 Importance : 378 p. Format : 19 x 27 cm ISBN/ISSN/EAN : 978-953-51-3578-4 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Statistiques [Termes IGN] estimation bayesienne [Termes IGN] filtrage bayésien [Termes IGN] inférence statistique [Termes IGN] méthode de Monte-Carlo par chaînes de Markov [Termes IGN] régression [Termes IGN] réseau bayesien Résumé : (éditeur) The range of Bayesian inference algorithms and their different applications has been greatly expanded since the first implementation of a Kalman filter by Stanley F. Schmidt for the Apollo program. Extended Kalman filters or particle filters are just some examples of these algorithms that have been extensively applied to logistics, medical services, search and rescue operations, or automotive safety, among others. This book takes a look at both theoretical foundations of Bayesian inference and practical implementations in different fields. It is intended as an introductory guide for the application of Bayesian inference in the fields of life sciences, engineering, and economics, as well as a source document of fundamentals for intermediate Bayesian readers. Note de contenu : 1- Bayesian inference application 2- Node-level conflict measures in Bayesian hierarchical models based on directed acyclic graphs 3- Classifying by Bayesian method and some applications 4- Hypothesis testing for high-dimensional problems 5- Bayesian vs frequentist power functions to determine the optimal sample size: testing one sample binomial proportion using exact methods 6- Converting graphic relationships into conditional probabilities in Bayesian network 7- Bayesian estimation of multivariate autoregressive hidden Markov model with application to breast cancer biomarker modeling 8- Bayesian model averaging and compromising in dose-response studies 9- Two examples of Bayesian evidence synthesis with the hierarchical meta-regression approach 10- Bayesian modeling in genetics and genomicsvvv 11- Bayesian two-stage robust causal modeling with instrumental variables using student's t distributions 12- Bayesian hypothesis testing: an alternative to null hypothesis significance testing (NHST) in psychology and social sciences 13- Bayesian inference and compressed sensing 14- Sparsity in Bayesian signal estimation 15- Dynamic Bayesian network for time-dependent classification problems in robotics 16- A Bayesian model for investment decisions in early ventures 17- Recent advances in nonlinear filtering with a financial application to derivatives hedging under incomplete information 18- Airlines content recommendations based on passengers' choice using Bayesian belief networks Numéro de notice : 25957 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.5772/66264 En ligne : https://doi.org/10.5772/66264 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96464