Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Beijesiskā regresija× | Koksas proporcionālās bīstamības regresija× | |
|---|---|---|
| Nozare≠ | Bajesa metodes | Dzīvildze |
| Saime≠ | Bayesian methods | Survival analysis |
| Izcelsmes gads≠ | — | 1972 |
| Autors≠ | — | Cox, D. R. |
| Tips≠ | Bayesian linear model | Semi-parametric hazard regression model |
| Pirmavots≠ | 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 | Cox, D. R. (1972). Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202. DOI ↗ |
| Citi nosaukumi≠ | bayesian linear regression, probabilistic regression, bayesian regresyon | cox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu |
| Saistītās≠ | 2 | 3 |
| Kopsavilkums≠ | 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. | 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. |
| ScholarGateDatu kopa ↗ |
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