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Metoda uzorkovanja po odsječcima×Bayesovska regresija×
PodručjeBayesovska statistikaBayesovska statistika
ObiteljBayesian methodsBayesian methods
Godina nastanka2003
TvoracRadford M. Neal
VrstaMCMC sampling algorithmBayesian linear model
Temeljni izvorNeal, R. M. (2003). Slice sampling (with discussion). Annals of Statistics, 31(3), 705–767. DOI ↗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
Drugi nazivislice sampler, Neal slice sampler, uniform slice sampling, auxiliary variable slice samplerbayesian linear regression, probabilistic regression, bayesian regresyon
Srodne42
SažetakSlice sampling is a Markov chain Monte Carlo (MCMC) algorithm introduced by Radford M. Neal in his 2003 Annals of Statistics paper. It generates samples from a target distribution by drawing uniformly from the region under the density curve — called the 'slice' — without requiring the user to specify a step-size or proposal distribution, making it self-tuning and broadly applicable for Bayesian posterior inference.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.
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ScholarGateUsporedite metode: Slice Sampling · Bayesian Regression. Preuzeto 2026-06-15 s https://scholargate.app/hr/compare