Practical Nonparametric and Semiparametric Bayesian Statistics (eBook, PDF)

Redaktion: Dey, Dipak D.; Sinha, Debajyoti; Müiler, Peter

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Springer US
• Seitenzahl: 392
• Erscheinungstermin: 6. Dezember 2012
• Englisch
• ISBN-13: 9781461217329
• Artikelnr.: 44043538

Autorenporträt

Dipak K. Dey is Head and Professor of Statistics at the University of Connecticut.

Inhaltsangabe

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.