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Campionamento per Fette×Regressione Bayesiana×
CampoBayesianoBayesiano
FamigliaBayesian methodsBayesian methods
Anno di origine2003
IdeatoreRadford M. Neal
TipoMCMC sampling algorithmBayesian linear model
Fonte seminaleNeal, 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
Aliasslice sampler, Neal slice sampler, uniform slice sampling, auxiliary variable slice samplerbayesian linear regression, probabilistic regression, bayesian regresyon
Correlati42
SintesiSlice 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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ScholarGateConfronta i metodi: Slice Sampling · Bayesian Regression. Consultato il 2026-06-15 da https://scholargate.app/it/compare