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Titlebook: Bayesian Analysis of Failure Time Data Using P-Splines; Matthias Kaeding Book 2015 Springer Fachmedien Wiesbaden 2015 Bayesian Statistics.

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期刊全稱Bayesian Analysis of Failure Time Data Using P-Splines
影響因子2023Matthias Kaeding
視頻videohttp://file.papertrans.cn/182/181826/181826.mp4
發(fā)行地址Publication in the field of natural sciences.Includes supplementary material:
學(xué)科分類BestMasters
圖書封面Titlebook: Bayesian Analysis of Failure Time Data Using P-Splines;  Matthias Kaeding Book 2015 Springer Fachmedien Wiesbaden 2015 Bayesian Statistics.
影響因子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.
Pindex Book 2015
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