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Regresión bayesiana×Regresión de Riesgos Proporcionales de Cox×
CampoBayesianoSupervivencia
FamiliaBayesian methodsSurvival analysis
Año de origen1972
Autor originalCox, D. R.
TipoBayesian linear modelSemi-parametric hazard regression model
Fuente seminalGelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A. & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955Cox, D. R. (1972). Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202. DOI ↗
Aliasbayesian linear regression, probabilistic regression, bayesian regresyoncox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu
Relacionados23
ResumenBayesian regression is a probabilistic version of linear regression that treats the model parameters as uncertain quantities. Instead of returning a single best-fit estimate, it combines prior knowledge with the observed data to produce a full posterior probability distribution for each parameter, from which credible intervals and predictions are read off.Cox proportional hazards regression, introduced by D. R. Cox in 1972, is a semi-parametric model that estimates how one or more covariates affect the hazard — the instantaneous rate of experiencing an event — while leaving the baseline hazard function unspecified. It is the standard multivariable method in survival analysis and produces hazard ratios that quantify the relative risk associated with each predictor.
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ScholarGateComparar métodos: Bayesian Regression · Cox Regression. Recuperado el 2026-06-18 de https://scholargate.app/es/compare