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Bayesian Analysis of Failure Time Data Using P-Splines
Matthias Kaeding
€ 74.89
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Description for Bayesian Analysis of Failure Time Data Using P-Splines
Paperback. Series: BestMasters. Num Pages: 119 pages, 23 black & white illustrations, 8 black & white tables, biography. BIC Classification: MBGL; PBT; PSD. Category: (P) Professional & Vocational. Dimension: 210 x 148 x 7. Weight in Grams: 171.
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 ... Read more
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 ... Read more
Product Details
Format
Paperback
Publication date
2014
Publisher
Springer Fachmedien Wiesbaden Germany
Number of pages
119
Condition
New
Series
BestMasters
Number of Pages
110
Place of Publication
Weisbaden, Germany
ISBN
9783658083922
SKU
V9783658083922
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About Matthias Kaeding
Matthias Kaeding obtained his Master of Science degree at the University of Bamberg in Survey Statistics.
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