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Practical Nonparametric and Semiparametric Bayesian Statistics
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Catalogue Information
Field name
Details
Dewey Class
519
Title
Practical Nonparametric and Semiparametric Bayesian Statistics ([EBook] /) / edited by Dipak Dey, Peter Müller, Debajyoti Sinha.
Added Personal Name
Dey, Dipak
editor.
Müller, Peter
editor.
Sinha, Debajyoti
editor.
Other name(s)
SpringerLink (Online service)
Publication
New York, NY : : Springer New York : : Imprint: Springer, , 1998.
Physical Details
XVI, 392 p. : online resource.
Series
Lecture Notes in Statistics
0930-0325 ; ; 133
ISBN
9781461217329
Summary Note
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.:
Contents note
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.
System details note
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users)
Internet Site
http://dx.doi.org/10.1007/978-1-4612-1732-9
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Subject References:
Applications of Mathematics
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Applied mathematics
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Engineering mathematics
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Mathematics
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Authors:
Dey, Dipak
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Müller, Peter
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Sinha, Debajyoti
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Corporate Authors:
SpringerLink (Online service)
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Series:
Lecture Notes in Statistics
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Classification:
519
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