2012, ISBN: 9783658083922

[ED: Taschenbuch], [PU: Springer Fachmedien Wiesbaden], Neuware - Matthias Kaeding discusses Bayesian methods for analyzing discrete and continuous failure times where the effect of time … Altro …

[ED: Taschenbuch], [PU: Springer Fachmedien Wiesbaden], Neuware - 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.- Besorgungstitel - vorauss. Lieferzeit 3-5 Tage., DE, [SC: 2.20], Neuware, gewerbliches Angebot, 210x148x7 mm, 120, [GW: 167g], Banküberweisung, Offene Rechnung, Kreditkarte, PayPal, Offene Rechnung (Vorkasse vorbehalten), Internationaler Versand<

2015, ISBN: 9783658083922

[ED: Softcover], [PU: Springer Fachmedien Wiesbaden / Springer Spektrum / Springer, Berlin], Matthias Kaeding discusses Bayesian methods for analyzing discrete and continuous failure time… Altro …

[ED: Softcover], [PU: Springer Fachmedien Wiesbaden / Springer Spektrum / Springer, Berlin], 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. 2015. 2015. ix, 110 S. IX, 110 p. 23 illus. 210 mm Versandfertig in 6-10 Tagen, DE, [SC: 0.00], Neuware, gewerbliches Angebot, Offene Rechnung (Vorkasse vorbehalten)<

2015, ISBN: 3658083921

[EAN: 9783658083922], Neubuch, [SC: 0.0], [PU: Springer Fachmedien Wiesbaden], BAYES-VERFAHREN; BAYESIANSTATISTICS; COXMODELL; FAILURETIMEANALYSIS; GIBBSSAMPLER; IWLSPROPOSALS, Druck auf … Altro …

[EAN: 9783658083922], Neubuch, [SC: 0.0], [PU: Springer Fachmedien Wiesbaden], BAYES-VERFAHREN; BAYESIANSTATISTICS; COXMODELL; FAILURETIMEANALYSIS; GIBBSSAMPLER; IWLSPROPOSALS, Druck auf Anfrage Neuware - Printed after ordering - 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. 120 pp. Englisch, Books<

2015, ISBN: 3658083921

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 fu… Altro …

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. Media Buch, 110 Seiten, Media > Books, Springer Spektrum, 2015<

2015, ISBN: 3658083921

2015 Kartoniert / Broschiert Bayes-Verfahren, Wahrscheinlichkeitsrechnung und Statistik, Stochastik, DV-gestützte Biologie/Bioinformatik, BayesianStatistics; CoxModell; FailureTimeAnaly… Altro …

2015 Kartoniert / Broschiert Bayes-Verfahren, Wahrscheinlichkeitsrechnung und Statistik, Stochastik, DV-gestützte Biologie/Bioinformatik, BayesianStatistics; CoxModell; FailureTimeAnalysis; Gibbssampler; IWLSProposals, mit Schutzumschlag 11, [PU:Springer Fachmedien Wiesbaden; Springer Fachmedien Wiesbaden GmbH]<