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000725001 019__ $$a903954260$$a908087543
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000725001 0247_ $$a10.1007/978-3-658-08393-9$$2doi
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000725001 050_4 $$aQA276$$b.K34 2015eb
000725001 08204 $$a519.5/46$$223
000725001 1001_ $$aKaeding, Matthias,$$eauthor.
000725001 24510 $$aBayesian analysis of failure time data using P-Splines$$h[electronic resource] /$$cMatthias Kaeding.
000725001 264_1 $$aWiesbaden :$$bSpringer Spektrum,$$c2015.
000725001 300__ $$a1 online resource (ix, 110 pages) :$$billustrations.
000725001 336__ $$atext$$btxt$$2rdacontent
000725001 337__ $$acomputer$$bc$$2rdamedia
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000725001 4901_ $$aBestMasters
000725001 504__ $$aIncludes bibliographical references.
000725001 5050_ $$aRelative Risk and Log-Location-Scale Family -- Bayesian P-Splines -- Discrete Time Models -- Continuous Time Models.
000725001 506__ $$aAccess limited to authorized users.
000725001 520__ $$aMatthias Kaeding discusses Bayesian methods for analyzing discrete and continuous failure times where the effect of time and/or covariates is modeled via P-splines and additional basic function expansions, allowing the replacement of linear effects by more general functions. The MCMC methodology for these models is presented in a unified framework and applied on data sets. Among others, existing algorithms for the grouped Cox and the piecewise exponential model under interval censoring are combined with a data augmentation step for the applications. The author shows that the resulting Gibbs sampler works well for the grouped Cox and is merely adequate for the piecewise exponential model. Contents Relative Risk and Log-Location-Scale Family Bayesian P-Splines Discrete Time Models Continuous Time Models Target Groups Researchers and students in the fields of statistics, engineering, and life sciences Practitioners in the fields of reliability engineering and data analysis involved with lifetimes The Author Matthias Kaeding obtained his Master of Science degree at the University of Bamberg in Survey Statistics.
000725001 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed January 12, 2015).
000725001 650_0 $$aFailure time data analysis.
000725001 650_0 $$aBayesian statistical decision theory.
000725001 77608 $$iPrint version:$$z9783658083922
000725001 830_0 $$aBestMasters.
000725001 852__ $$bebk
000725001 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-658-08393-9$$zOnline Access$$91397441.1
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