| Titre : |
Bayesian thinking : modeling and computation |
| Type de document : |
texte imprimé |
| Auteurs : |
Dey, Dipak Kumar, Éditeur scientifique ; Rao, Calyampudi Radhakrishna, Éditeur scientifique |
| Editeur : |
Amsterdam : Elsevier |
| Année de publication : |
2005 |
| Collection : |
Handbook of statistics, ISSN 0169-7161 num. 25 |
| Importance : |
XX, 1041 p. |
| Présentation : |
ill. |
| Format : |
25 cm |
| ISBN/ISSN/EAN : |
978-0-444-51539-1 |
| Note générale : |
Notes bibliogr. - Index |
| Langues : |
Anglais (eng) |
| Mots-clés : |
Bayesian statistical decision theory
Nonparametric statistics
Statistique bayésienne
Statistique non paramétrique -- Méthodologie
Prise de décision |
| Index. décimale : |
519.2 (035) Probabilités. Statistique mathématique (Handbook) |
| Résumé : |
This volume describes how to develop Bayesian thinking, modelling and computation both from philosophical, methodological and application point of view. It further describes parametric and nonparametric Bayesian methods for modelling and how to use modern computational methods to summarize inferences using simulation. The book covers wide range of topics including objective and subjective Bayesian inferences with a variety of applications in modelling categorical, survival, spatial, spatiotemporal, Epidemiological, software reliability, small area and micro array data. The book concludes with a chapter on how to teach Bayesian thoughts to nonstatisticians. |
| Note de contenu : |
Summary :
1- Bayesian inference for causal effects
2- Reference analysis
3- Probability matching priors
4- Model selection and hypothesis testing based on objective probabilities and Bayes factors
5- Role of P-values and other measures of evidence in Bayesian analysis
6- Bayesian model checking and model diagnostics
7- The elimination of nuisance parameters
8- Bayesian estimation of multivariate location parameters |
Bayesian thinking : modeling and computation [texte imprimé] / Dey, Dipak Kumar, Éditeur scientifique ; Rao, Calyampudi Radhakrishna, Éditeur scientifique . - Amsterdam : Elsevier, 2005 . - XX, 1041 p. : ill. ; 25 cm. - ( Handbook of statistics, ISSN 0169-7161; 25) . ISBN : 978-0-444-51539-1 Notes bibliogr. - Index Langues : Anglais ( eng)
| Mots-clés : |
Bayesian statistical decision theory
Nonparametric statistics
Statistique bayésienne
Statistique non paramétrique -- Méthodologie
Prise de décision |
| Index. décimale : |
519.2 (035) Probabilités. Statistique mathématique (Handbook) |
| Résumé : |
This volume describes how to develop Bayesian thinking, modelling and computation both from philosophical, methodological and application point of view. It further describes parametric and nonparametric Bayesian methods for modelling and how to use modern computational methods to summarize inferences using simulation. The book covers wide range of topics including objective and subjective Bayesian inferences with a variety of applications in modelling categorical, survival, spatial, spatiotemporal, Epidemiological, software reliability, small area and micro array data. The book concludes with a chapter on how to teach Bayesian thoughts to nonstatisticians. |
| Note de contenu : |
Summary :
1- Bayesian inference for causal effects
2- Reference analysis
3- Probability matching priors
4- Model selection and hypothesis testing based on objective probabilities and Bayes factors
5- Role of P-values and other measures of evidence in Bayesian analysis
6- Bayesian model checking and model diagnostics
7- The elimination of nuisance parameters
8- Bayesian estimation of multivariate location parameters |
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