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Bayesian Analysis of Failure Time Data Using P-Splines (BestMasters) - Softcover

Book 5 of 91: BestMasters

Kaeding, Matthias

 
9783658083922: Bayesian Analysis of Failure Time Data Using P-Splines (BestMasters)
Softcover
ISBN 10: 3658083921 ISBN 13: 9783658083922
Publisher: Springer Spektrum, 2015

Synopsis

Matthias Kaeding discusses Bayesian methods for analyzing discrete and continuous failure times where the effect of time and/or covariates is modeled via P-splines and additional basic function expansions, allowing the replacement of linear effects by more general functions. The MCMC methodology for these models is presented in a unified framework and applied on data sets. Among others, existing algorithms for the grouped Cox and the piecewise exponential model under interval censoring are combined with a data augmentation step for the applications. The author shows that the resulting Gibbs sampler works well for the grouped Cox and is merely adequate for the piecewise exponential model.

"synopsis" may belong to another edition of this title.

About the Author

Matthias Kaeding obtained his Master of Science degree at the University of Bamberg in Survey Statistics.

From the Back Cover

Matthias Kaeding discusses Bayesian methods for analyzing discrete and continuous failure times where the effect of time and/or covariates is modeled via P-splines and additional basic function expansions, allowing the replacement of linear effects by more general functions. The MCMC methodology for these models is presented in a unified framework and applied on data sets. Among others, existing algorithms for the grouped Cox and the piecewise exponential model under interval censoring are combined with a data augmentation step for the applications. The author shows that the resulting Gibbs sampler works well for the grouped Cox and is merely adequate for the piecewise exponential model.

Contents

  • Relative Risk and Log-Location-Scale Family
  • Bayesian P-Splines
  • Discrete Time Models
  • Continuous Time Models

Target Groups

  • Researchers and students in the fields of statistics, engineering, and life sciences
  • Practitioners in the fields of reliability engineering and data analysis involved with lifetimes

The Author

Matthias Kaeding obtained his Master of Science degree at the University of Bamberg in Survey Statistics.

"About this title" may belong to another edition of this title.

Publisher
Springer Spektrum
Publication date
2015
Language
English
ISBN 10 
3658083921
ISBN 13 
9783658083922
Binding
Paperback
Number of pages
119