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Bayes' regressioon×Kaplan-Meieri elulemuse estimaator×
ValdkondBayesi meetodidElukestusanalüüs
PerekondBayesian methodsSurvival analysis
Tekkeaasta1958
LoojaKaplan, E. L. & Meier, P.
TüüpBayesian linear modelNon-parametric survival estimator
AlgallikasGelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A. & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗
Rööpnimetusedbayesian linear regression, probabilistic regression, bayesian regresyonproduct-limit estimator, km curve, kaplan-meier sağkalım analizi
Seotud22
KokkuvõteBayesian 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.The Kaplan-Meier estimator, introduced by Kaplan and Meier in 1958, is a non-parametric method that estimates the survival curve — the probability of remaining event-free over time — from right-censored time-to-event data. The log-rank test is the companion procedure used to compare survival curves between groups.
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ScholarGateVõrdle meetodeid: Bayesian Regression · Kaplan-Meier. Loetud 2026-06-18 aadressilt https://scholargate.app/et/compare