Matches in DBpedia 2014 for { <http://dbpedia.org/resource/Gibbs_sampling> ?p ?o }
Showing triples 1 to 31 of
31
with 100 triples per page.
- Gibbs_sampling abstract "In statistics and in statistical physics, Gibbs sampling or a Gibbs sampler is a Markov chain Monte Carlo (MCMC) algorithm for obtaining a sequence of observations which are approximated from a specified multivariate probability distribution (i.e. from the joint probability distribution of two or more random variables), when direct sampling is difficult. This sequence can be used to approximate the joint distribution (e.g., to generate a histogram of the distribution); to approximate the marginal distribution of one of the variables, or some subset of the variables (for example, the unknown parameters or latent variables); or to compute an integral (such as the expected value of one of the variables). Typically, some of the variables correspond to observations whose values are known, and hence do not need to be sampled.Gibbs sampling is commonly used as a means of statistical inference, especially Bayesian inference. It is a randomized algorithm (i.e. an algorithm that makes use of random numbers, and hence may produce different results each time it is run), and is an alternative to deterministic algorithms for statistical inference such as variational Bayes or the expectation-maximization algorithm (EM).As with other MCMC algorithms, Gibbs sampling generates a Markov chain of samples, each of which is correlated with nearby samples. As a result, care must be taken if independent samples are desired (typically by thinning the resulting chain of samples by only taking every nth value, e.g. every 100th value). In addition (again, as in other MCMC algorithms), samples from the beginning of the chain (the burn-in period) may not accurately represent the desired distribution.[citation needed]".
- Gibbs_sampling wikiPageExternalLink gibbs.html.
- Gibbs_sampling wikiPageExternalLink ps.
- Gibbs_sampling wikiPageExternalLink book.html.
- Gibbs_sampling wikiPageExternalLink w.
- Gibbs_sampling wikiPageExternalLink MARKOV.
- Gibbs_sampling wikiPageID "509709".
- Gibbs_sampling wikiPageRevisionID "601320792".
- Gibbs_sampling hasPhotoCollection Gibbs_sampling.
- Gibbs_sampling subject Category:Markov_chain_Monte_Carlo.
- Gibbs_sampling comment "In statistics and in statistical physics, Gibbs sampling or a Gibbs sampler is a Markov chain Monte Carlo (MCMC) algorithm for obtaining a sequence of observations which are approximated from a specified multivariate probability distribution (i.e. from the joint probability distribution of two or more random variables), when direct sampling is difficult.".
- Gibbs_sampling label "Amostragem de Gibbs".
- Gibbs_sampling label "Campionamento di Gibbs".
- Gibbs_sampling label "Gibbs sampling".
- Gibbs_sampling label "Gibbs-Sampling".
- Gibbs_sampling label "Muestreo de Gibbs".
- Gibbs_sampling label "Échantillonnage de Gibbs".
- Gibbs_sampling label "Семплирование по Гиббсу".
- Gibbs_sampling label "ギブスサンプリング".
- Gibbs_sampling sameAs Gibbs-Sampling.
- Gibbs_sampling sameAs Muestreo_de_Gibbs.
- Gibbs_sampling sameAs Échantillonnage_de_Gibbs.
- Gibbs_sampling sameAs Campionamento_di_Gibbs.
- Gibbs_sampling sameAs ギブスサンプリング.
- Gibbs_sampling sameAs 기브스_표집.
- Gibbs_sampling sameAs Amostragem_de_Gibbs.
- Gibbs_sampling sameAs m.02jxh7.
- Gibbs_sampling sameAs Q1191905.
- Gibbs_sampling sameAs Q1191905.
- Gibbs_sampling wasDerivedFrom Gibbs_sampling?oldid=601320792.
- Gibbs_sampling isPrimaryTopicOf Gibbs_sampling.