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Bayesovská Coxova regresia×Bayesovský zovšeobecnený lineárny model×
OdborŠtatistikaŠtatistika
RodinaRegression modelRegression model
Rok vzniku1972 (Cox PH); 2001 (Bayesian treatment)1989 (GLM); 1995 (Bayesian BDA)
TvorcaCox (1972) for the base model; Bayesian formulation by Sinha, Chen & Ghosh (1990s); comprehensive treatment by Ibrahim, Chen & Sinha (2001)McCullagh & Nelder (GLM framework); Bayesian treatment formalized by Gelman et al.
TypSurvival regressionBayesian regression model
Pôvodný zdrojIbrahim, J. G., Chen, M.-H., & Sinha, D. (2001). Bayesian Survival Analysis. Springer. ISBN: 978-0387952772Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955
Ďalšie názvyBayesian Cox PH model, Bayesian proportional hazards model, Bayesian survival regression, BCoxBayesian GLM, Bayesian GLIM, Bayesian generalized linear regression, Bayes GLM
Príbuzné66
ZhrnutieBayesian Cox regression combines the Cox proportional hazards model for time-to-event data with Bayesian inference. Instead of point estimates, it produces full posterior distributions over the hazard ratios, naturally incorporating prior knowledge and providing coherent uncertainty quantification even with small samples or informative censoring.A Bayesian Generalized Linear Model (Bayesian GLM) extends the classical GLM framework by placing prior distributions on the regression coefficients and updating them with data via Bayes' theorem. This yields a full posterior distribution over parameters rather than single point estimates, enabling richer uncertainty quantification and principled incorporation of prior knowledge for any exponential-family outcome.
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ScholarGatePorovnať metódy: Bayesian Cox Regression · Bayesian Generalized Linear Model. Získané 2026-06-15 z https://scholargate.app/sk/compare