Knygos.lt nariams
Knygos.lt nariams
- Išsiųsime per 12–18 d.d.
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- Autorius: Matthias Kaeding
- Leidėjas: Springer Spektrum
- Metai: 2015
- Puslapiai: 110
- ISBN-10: 3658083921
- ISBN-13: 9783658083922
- Formatas: 14.8 x 21 x 0.7 cm, minkšti viršeliai
- Kalba: Anglų
Bayesian Analysis of Failure Time Data Using P-Splines (el. knyga) (skaityta knyga) | knygos.lt
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Aprašymas
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.
- Autorius: Matthias Kaeding
- Leidėjas: Springer Spektrum
- Metai: 2015
- Puslapiai: 110
- ISBN-10: 3658083921
- ISBN-13: 9783658083922
- Formatas: 14.8 x 21 x 0.7 cm, minkšti viršeliai
- Kalba: Anglų
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.
Atsiliepimai