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  • 1
    Book
    Book
    New York [u.a.] :Springer,
    UID:
    almahu_BV013921698
    Format: XIV, 479 S. : , graph. Darst.
    ISBN: 0-387-95277-2
    Series Statement: Springer series in statistics
    Language: English
    Subjects: Economics , Mathematics
    RVK:
    RVK:
    Keywords: Zuverlässigkeitstheorie ; Bayes-Verfahren ; Überlebenszeit ; Bayes-Verfahren
    Author information: Chen, Ming-Hui, 1961-
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    UID:
    almahu_9947363210702882
    Format: XIV, 480 p. , online resource.
    ISBN: 9781475734478
    Series Statement: Springer Series in Statistics,
    Content: Survival analysis arises in many fields of study including medicine, biology, engineering, public health, epidemiology, and economics. This book provides a comprehensive treatment of Bayesian survival analysis. Several topics are addressed, including parametric models, semiparametric models based on prior processes, proportional and non-proportional hazards models, frailty models, cure rate models, model selection and comparison, joint models for longitudinal and survival data, models with time varying covariates, missing covariate data, design and monitoring of clinical trials, accelerated failure time models, models for mulitivariate survival data, and special types of hierarchial survival models. Also various censoring schemes are examined including right and interval censored data. Several additional topics are discussed, including noninformative and informative prior specificiations, computing posterior qualities of interest, Bayesian hypothesis testing, variable selection, model selection with nonnested models, model checking techniques using Bayesian diagnostic methods, and Markov chain Monte Carlo (MCMC) algorithms for sampling from the posteiror and predictive distributions. The book presents a balance between theory and applications, and for each class of models discussed, detailed examples and analyses from case studies are presented whenever possible. The applications are all essentially from the health sciences, including cancer, AIDS, and the environment. The book is intended as a graduate textbook or a reference book for a one semester course at the advanced masters or Ph.D. level. This book would be most suitable for second or third year graduate students in statistics or biostatistics. It would also serve as a useful reference book for applied or theoretical researchers as well as practitioners.
    Note: 1 Introduction -- 2 Parametric Models -- 3 Semiparametric Models -- 4 Frailty Models -- 5 Cure Rate Models -- 6 Model Comparison -- 7 Joint Models for Longitudinal and Survival Data -- 8 Missing Covariate Data -- 9 Design and Monitoring of Randomized Clinical Trials -- 10 Other Topics -- List of Distributions -- References -- Author Index.
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9781441929334
    Language: English
    URL: Volltext  (lizenzpflichtig)
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  • 3
    UID:
    almahu_9947362854702882
    Format: XVI, 392 p. , online resource.
    ISBN: 9781461217329
    Series Statement: Lecture Notes in Statistics, 133
    Content: 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.
    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.
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9780387985176
    Language: English
    Keywords: Aufsatzsammlung
    Library Location Call Number Volume/Issue/Year Availability
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