विधियों की तुलना करें

	बेयसियन रिग्रेशन	वेइबुल पैरामीट्रिक सर्वाइवल रिग्रेशन
क्षेत्र	बायेसियन	उत्तरजीविता
परिवार	Bayesian methods	Survival analysis
उद्भव वर्ष	—	1951
प्रवर्तक	—	Waloddi Weibull
प्रकार	Bayesian linear model	Fully parametric survival regression model
मौलिक स्रोत	Gelman, 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	Kalbfleisch, J. D. & Prentice, R. L. (2002). The Statistical Analysis of Failure Time Data (2nd ed.). Wiley.
उपनाम	bayesian linear regression, probabilistic regression, bayesian regresyon	weibull aft model, weibull survival model, parametric survival regression, Weibull Regresyonu — Parametrik Hayatta Kalma
संबंधित	2	4
सारांश	Bayesian 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.	Weibull regression is a fully parametric survival model, formalised by Kalbfleisch and Prentice, that assumes survival times follow a Weibull distribution. A shape parameter controls whether the hazard increases, decreases, or remains constant over time, while covariates shift the scale of the distribution to express how predictors affect survival.