Bayesian thinking (2005)

Public ISBD 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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Linear statistical inference and its applications / Rao, Calyampudi Radhakrishna (1973)

Public ISBD Titre : Linear statistical inference and its applications Type de document : texte imprimé Auteurs : Rao, Calyampudi Radhakrishna, Auteur Editeur : New York : John Wiley & Sons Année de publication : 1973 Collection : Wiley series in probability and mathematical statistics. Probability and mathematical statistics Importance : XX-625 p. Présentation : ill. Format : 24 cm ISBN/ISSN/EAN : 978-0-471-70823-0 Note générale : Bibliogr. en fin de chapitres. Index Langues : Anglais (eng) Mots-clés : Statistique mathématique Mathematical statistics Index. décimale : 519.21 Théorie des probabilités.Processus stochastiques Note de contenu : Sommaire: 1. Algebra of vectors and matrices 2. Probability theory, tools and techniques 3. Continuos probability models 4. The theory of least squares and analysis of variance 5. Criteria and methods of estimation 6. Large sample theory and méthods 7. Theory of statistical inference 8. Multivariate analysis Linear statistical inference and its applications [texte imprimé] / Rao, Calyampudi Radhakrishna, Auteur . - New York : John Wiley & Sons, 1973 . - XX-625 p. : ill. ; 24 cm. - (Wiley series in probability and mathematical statistics. Probability and mathematical statistics) . ISBN : 978-0-471-70823-0 Bibliogr. en fin de chapitres. Index Langues : Anglais (eng) Mots-clés : Statistique mathématique Mathematical statistics Index. décimale : 519.21 Théorie des probabilités.Processus stochastiques Note de contenu : Sommaire: 1. Algebra of vectors and matrices 2. Probability theory, tools and techniques 3. Continuos probability models 4. The theory of least squares and analysis of variance 5. Criteria and methods of estimation 6. Large sample theory and méthods 7. Theory of statistical inference 8. Multivariate analysis

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Stochastic processes (2003)

Public ISBD Titre : Stochastic processes : modelling and simulation Type de document : texte imprimé Auteurs : Shanbhag, D. N., Éditeur scientifique ; Rao, Calyampudi Radhakrishna, Éditeur scientifique Editeur : Amsterdam : Elsevier Année de publication : 2003 Collection : Handbook of statistics, ISSN 0169-7161 num. 21 Importance : XVII, 1000 p. Présentation : ill. Format : 25 cm ISBN/ISSN/EAN : 978-0-444-50013-7 Note générale : Notes bibliogr. - Index Langues : Anglais (eng) Mots-clés : Processus stochastiques Modèles mathématiques Simulation par ordinateur Index. décimale : 519.2 (035) Probabilités. Statistique mathématique (Handbook) Résumé : This is a sequel to volume 19 of Handbook of Statistics on Stochastic Processes: Modelling and Simulation. It is concerned mainly with the theme of reviewing and in some cases, unifying with new ideas the different lines of research and developments in stochastic processes of applied flavour. This volume consists of 23 chapters addressing various topics in stochastic processes. These include, among others, those on manufacturing systems, random graphs, reliability, epidemic modelling, self-similar processes, empirical processes, time series models, extreme value theory, applications of Markov chains, modelling with Monte carlo techniques, and stochastic processes in subjects such as engineering, telecommunications, biology, astronomy and chemistry. (A complete list of the topics addressed in the volume is available from the "Contents" of the volume.) An attempt is made to cover in this volume, as in the case of its predecessor, as many topics as possible. Among various issues considered in this volume, there are those concerned in particular with modelling, simulation techniques and numerical methods concerned with stochastic processes. The scope of the project involving this volume as well as volume 19 is already clarified in the "Preface" of volume 19. The present volume completes the aim of the project, and it should serve as an aid to students, teachers, researchers and practitioners interested in applied stochastic processes. Note de contenu : Summary : 1. Modeling and Numerical Methods in Manufacturing Systems using Control Theory 2. Models of Random Graphs and their Applications 3. Locally Self-Similar Processes and their Wavelet Analysis 4. Stochastic Models for DNA Replications 5. An Empirical Process with Applications to Test Exponential and Geometric Models 6. Patterns of Sequences of Random Events 7. Stochastic Models in Telecommunications for Optimal Design, Control, and Performance Evaluation Stochastic processes : modelling and simulation [texte imprimé] / Shanbhag, D. N., Éditeur scientifique ; Rao, Calyampudi Radhakrishna, Éditeur scientifique . - Amsterdam : Elsevier, 2003 . - XVII, 1000 p. : ill. ; 25 cm. - (Handbook of statistics, ISSN 0169-7161; 21) . ISBN : 978-0-444-50013-7 Notes bibliogr. - Index Langues : Anglais (eng) Mots-clés : Processus stochastiques Modèles mathématiques Simulation par ordinateur Index. décimale : 519.2 (035) Probabilités. Statistique mathématique (Handbook) Résumé : This is a sequel to volume 19 of Handbook of Statistics on Stochastic Processes: Modelling and Simulation. It is concerned mainly with the theme of reviewing and in some cases, unifying with new ideas the different lines of research and developments in stochastic processes of applied flavour. This volume consists of 23 chapters addressing various topics in stochastic processes. These include, among others, those on manufacturing systems, random graphs, reliability, epidemic modelling, self-similar processes, empirical processes, time series models, extreme value theory, applications of Markov chains, modelling with Monte carlo techniques, and stochastic processes in subjects such as engineering, telecommunications, biology, astronomy and chemistry. (A complete list of the topics addressed in the volume is available from the "Contents" of the volume.) An attempt is made to cover in this volume, as in the case of its predecessor, as many topics as possible. Among various issues considered in this volume, there are those concerned in particular with modelling, simulation techniques and numerical methods concerned with stochastic processes. The scope of the project involving this volume as well as volume 19 is already clarified in the "Preface" of volume 19. The present volume completes the aim of the project, and it should serve as an aid to students, teachers, researchers and practitioners interested in applied stochastic processes. Note de contenu : Summary : 1. Modeling and Numerical Methods in Manufacturing Systems using Control Theory 2. Models of Random Graphs and their Applications 3. Locally Self-Similar Processes and their Wavelet Analysis 4. Stochastic Models for DNA Replications 5. An Empirical Process with Applications to Test Exponential and Geometric Models 6. Patterns of Sequences of Random Events 7. Stochastic Models in Telecommunications for Optimal Design, Control, and Performance Evaluation

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