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Cover: 9780387985176 | Practical Nonparametric and Semiparametric Bayesian Statistics | Buch
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Practical Nonparametric and Semiparametric Bayesian Statistics
Taschenbuch von Dipak D. Dey (u. a.)
Sprache: Englisch

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Beschreibung
A compilation of original articles by Bayesian experts, this volume presents perspectives on recent developments on nonparametric and semiparametric methods in Bayesian statistics. The articles discuss how to conceptualize and develop Bayesian models using rich classes of nonparametric and semiparametric methods, how to use modern computational tools to summarize inferences, and how to apply these methodologies through the analysis of case studies.
A compilation of original articles by Bayesian experts, this volume presents perspectives on recent developments on nonparametric and semiparametric methods in Bayesian statistics. The articles discuss how to conceptualize and develop Bayesian models using rich classes of nonparametric and semiparametric methods, how to use modern computational tools to summarize inferences, and how to apply these methodologies through the analysis of case studies.
Zusammenfassung
Nonparametric and semiparametric statistical methods are attractive to researchers in a large number of fields, including pharmaceuticals, medical and public health centers, financial institutions, and environmental monitoring centers. This survey volume presents both the theoretical and applied aspects of these methods, and the range of articles from expository to original research will make it of interest to people with a wide range of statistical backgrounds.
Inhaltsverzeichnis
I Dirichlet and Related Processes.- 1 Computing Nonparametric Hierarchical Models.- 2 Computational Methods for Mixture of Dirichlet Process Models.- 3 Nonparametric Bayes Methods Using Predictive Updating.- 4 Dynamic Display of Changing Posterior in Bayesian Survival Analysis.- 5 Semiparametric Bayesian Methods for Random Effects Models.- 6 Nonparametric Bayesian Group Sequential Design.- II Modeling Random Functions.- 7 Wavelet-Based Nonparametric Bayes Methods.- 8 Nonparametric Estimation of Irregular Functions with Independent or Autocorrelated Errors.- 9 Feedforward Neural Networks for Nonparametric Regression.- III Levy and Related Processes.- 10 Survival Analysis Using Semiparametric Bayesian Methods.- 11 Bayesian Nonparametric and Covariate Analysis of Failure Time Data.- 12 Simulation of Lévy Random Fields.- 13 Sampling Methods for Bayesian Nonparametric Inference Involving Stochastic Processes.- 14 Curve and Surface Estimation Using Dynamic Step Functions.- IV Prior Elicitation and Asymptotic Properties 15 Prior Elicitation for Semiparametric Bayesian Survival Analysis.- 16 Asymptotic Properties of Nonparametric Bayesian Procedures.- 17 Modeling Travel Demand in Portland, Oregon.- 18 Semiparametric PK/PD Models.- 19 A Bayesian Model for Fatigue Crack Growth.- 20 A Semiparametric Model for Labor Earnings Dynamics.
Details
Erscheinungsjahr: 1998
Fachbereich: Allgemeines
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 392
Reihe: Lecture Notes in Statistics
Inhalt: xvi
392 S.
ISBN-13: 9780387985176
ISBN-10: 0387985174
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Redaktion: Dey, Dipak D.
Sinha, Debajyoti
Müiler, Peter
Herausgeber: Dipak D Dey/Peter MüIler/Debajyoti Sinha
Auflage: 1998
Hersteller: Springer New York
Springer US, New York, N.Y.
Lecture Notes in Statistics
Maße: 235 x 155 x 22 mm
Von/Mit: Dipak D. Dey (u. a.)
Erscheinungsdatum: 28.05.1998
Gewicht: 0,593 kg
preigu-id: 102941303
Zusammenfassung
Nonparametric and semiparametric statistical methods are attractive to researchers in a large number of fields, including pharmaceuticals, medical and public health centers, financial institutions, and environmental monitoring centers. This survey volume presents both the theoretical and applied aspects of these methods, and the range of articles from expository to original research will make it of interest to people with a wide range of statistical backgrounds.
Inhaltsverzeichnis
I Dirichlet and Related Processes.- 1 Computing Nonparametric Hierarchical Models.- 2 Computational Methods for Mixture of Dirichlet Process Models.- 3 Nonparametric Bayes Methods Using Predictive Updating.- 4 Dynamic Display of Changing Posterior in Bayesian Survival Analysis.- 5 Semiparametric Bayesian Methods for Random Effects Models.- 6 Nonparametric Bayesian Group Sequential Design.- II Modeling Random Functions.- 7 Wavelet-Based Nonparametric Bayes Methods.- 8 Nonparametric Estimation of Irregular Functions with Independent or Autocorrelated Errors.- 9 Feedforward Neural Networks for Nonparametric Regression.- III Levy and Related Processes.- 10 Survival Analysis Using Semiparametric Bayesian Methods.- 11 Bayesian Nonparametric and Covariate Analysis of Failure Time Data.- 12 Simulation of Lévy Random Fields.- 13 Sampling Methods for Bayesian Nonparametric Inference Involving Stochastic Processes.- 14 Curve and Surface Estimation Using Dynamic Step Functions.- IV Prior Elicitation and Asymptotic Properties 15 Prior Elicitation for Semiparametric Bayesian Survival Analysis.- 16 Asymptotic Properties of Nonparametric Bayesian Procedures.- 17 Modeling Travel Demand in Portland, Oregon.- 18 Semiparametric PK/PD Models.- 19 A Bayesian Model for Fatigue Crack Growth.- 20 A Semiparametric Model for Labor Earnings Dynamics.
Details
Erscheinungsjahr: 1998
Fachbereich: Allgemeines
Genre: Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 392
Reihe: Lecture Notes in Statistics
Inhalt: xvi
392 S.
ISBN-13: 9780387985176
ISBN-10: 0387985174
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Redaktion: Dey, Dipak D.
Sinha, Debajyoti
Müiler, Peter
Herausgeber: Dipak D Dey/Peter MüIler/Debajyoti Sinha
Auflage: 1998
Hersteller: Springer New York
Springer US, New York, N.Y.
Lecture Notes in Statistics
Maße: 235 x 155 x 22 mm
Von/Mit: Dipak D. Dey (u. a.)
Erscheinungsdatum: 28.05.1998
Gewicht: 0,593 kg
preigu-id: 102941303
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