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- Author: Matthias Kaeding
- Publisher: Springer Spektrum
- Year: 2015
- Pages: 110
- ISBN-10: 3658083921
- ISBN-13: 9783658083922
- Format: 14.8 x 21 x 0.7 cm, minkšti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
Bayesian Analysis of Failure Time Data Using P-Splines (e-book) (used book) | bookbook.eu
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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.
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- Author: Matthias Kaeding
- Publisher: Springer Spektrum
- Year: 2015
- Pages: 110
- ISBN-10: 3658083921
- ISBN-13: 9783658083922
- Format: 14.8 x 21 x 0.7 cm, minkšti viršeliai
- Language: English English
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.
Reviews