FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W1625591031> ?p ?o ?g. }

• W1625591031 endingPage "53" @default.
• W1625591031 startingPage "44" @default.
• W1625591031 abstract "We investigate the class of σ-stable Poisson–Kingman random probability measures (RPMs) in the context of Bayesian nonparametric mixture modeling. This is a large class of discrete RPMs, which encompasses most of the popular discrete RPMs used in Bayesian nonparametrics, such as the Dirichlet process, Pitman–Yor process, the normalized inverse Gaussian process, and the normalized generalized Gamma process. We show how certain sampling properties and marginal characterizations of σ-stable Poisson–Kingman RPMs can be usefully exploited for devising a Markov chain Monte Carlo (MCMC) algorithm for performing posterior inference with a Bayesian nonparametric mixture model. Specifically, we introduce a novel and efficient MCMC sampling scheme in an augmented space that has a small number of auxiliary variables per iteration. We apply our sampling scheme to a density estimation and clustering tasks with unidimensional and multidimensional datasets, and compare it against competing MCMC sampling schemes. Supplementary materials for this article are available online." @default.
• W1625591031 created "2016-06-24" @default.
• W1625591031 creator A5002000099 @default.
• W1625591031 creator A5064373793 @default.
• W1625591031 creator A5083953277 @default.
• W1625591031 date "2017-01-02" @default.
• W1625591031 modified "2023-09-24" @default.
• W1625591031 title "A Marginal Sampler for σ-Stable Poisson–Kingman Mixture Models" @default.
• W1625591031 cites W1560385679 @default.
• W1625591031 cites W1807780152 @default.
• W1625591031 cites W1967318355 @default.
• W1625591031 cites W1969161020 @default.
• W1625591031 cites W1971807270 @default.
• W1625591031 cites W1997158470 @default.
• W1625591031 cites W2006043936 @default.
• W1625591031 cites W2011342110 @default.
• W1625591031 cites W2023744191 @default.
• W1625591031 cites W2025952763 @default.
• W1625591031 cites W2031964861 @default.
• W1625591031 cites W2048370764 @default.
• W1625591031 cites W2051698309 @default.
• W1625591031 cites W2053405531 @default.
• W1625591031 cites W2060434905 @default.
• W1625591031 cites W2063390378 @default.
• W1625591031 cites W2065392216 @default.
• W1625591031 cites W2069429561 @default.
• W1625591031 cites W2072169887 @default.
• W1625591031 cites W2079501320 @default.
• W1625591031 cites W2080972498 @default.
• W1625591031 cites W2086566242 @default.
• W1625591031 cites W2087309226 @default.
• W1625591031 cites W2089484716 @default.
• W1625591031 cites W2091797506 @default.
• W1625591031 cites W2101998432 @default.
• W1625591031 cites W2109614047 @default.
• W1625591031 cites W2118942461 @default.
• W1625591031 cites W2146915717 @default.
• W1625591031 cites W2150473224 @default.
• W1625591031 cites W2151388649 @default.
• W1625591031 cites W2152977846 @default.
• W1625591031 cites W263845233 @default.
• W1625591031 cites W3101682570 @default.
• W1625591031 cites W3103279442 @default.
• W1625591031 cites W32980360 @default.
• W1625591031 cites W4247690662 @default.
• W1625591031 doi "https://doi.org/10.1080/10618600.2015.1110526" @default.
• W1625591031 hasPublicationYear "2017" @default.
• W1625591031 type Work @default.
• W1625591031 sameAs 1625591031 @default.
• W1625591031 citedByCount "10" @default.
• W1625591031 countsByYear W16255910312014 @default.
• W1625591031 countsByYear W16255910312015 @default.
• W1625591031 countsByYear W16255910312016 @default.
• W1625591031 countsByYear W16255910312017 @default.
• W1625591031 countsByYear W16255910312018 @default.
• W1625591031 countsByYear W16255910312020 @default.
• W1625591031 countsByYear W16255910312021 @default.
• W1625591031 countsByYear W16255910312022 @default.
• W1625591031 crossrefType "journal-article" @default.
• W1625591031 hasAuthorship W1625591031A5002000099 @default.
• W1625591031 hasAuthorship W1625591031A5064373793 @default.
• W1625591031 hasAuthorship W1625591031A5083953277 @default.
• W1625591031 hasBestOaLocation W16255910312 @default.
• W1625591031 hasConcept C105795698 @default.
• W1625591031 hasConcept C106131492 @default.
• W1625591031 hasConcept C107673813 @default.
• W1625591031 hasConcept C111350023 @default.
• W1625591031 hasConcept C140779682 @default.
• W1625591031 hasConcept C158424031 @default.
• W1625591031 hasConcept C170593435 @default.
• W1625591031 hasConcept C2781280628 @default.
• W1625591031 hasConcept C28826006 @default.
• W1625591031 hasConcept C31972630 @default.
• W1625591031 hasConcept C33923547 @default.
• W1625591031 hasConcept C41008148 @default.
• W1625591031 hasConcept C61224824 @default.
• W1625591031 hasConcept C73555534 @default.
• W1625591031 hasConcept C79495835 @default.
• W1625591031 hasConceptScore W1625591031C105795698 @default.
• W1625591031 hasConceptScore W1625591031C106131492 @default.
• W1625591031 hasConceptScore W1625591031C107673813 @default.
• W1625591031 hasConceptScore W1625591031C111350023 @default.
• W1625591031 hasConceptScore W1625591031C140779682 @default.
• W1625591031 hasConceptScore W1625591031C158424031 @default.
• W1625591031 hasConceptScore W1625591031C170593435 @default.
• W1625591031 hasConceptScore W1625591031C2781280628 @default.
• W1625591031 hasConceptScore W1625591031C28826006 @default.
• W1625591031 hasConceptScore W1625591031C31972630 @default.
• W1625591031 hasConceptScore W1625591031C33923547 @default.
• W1625591031 hasConceptScore W1625591031C41008148 @default.
• W1625591031 hasConceptScore W1625591031C61224824 @default.
• W1625591031 hasConceptScore W1625591031C73555534 @default.
• W1625591031 hasConceptScore W1625591031C79495835 @default.
• W1625591031 hasIssue "1" @default.
• W1625591031 hasLocation W16255910311 @default.
• W1625591031 hasLocation W16255910312 @default.
• W1625591031 hasLocation W16255910313 @default.
• W1625591031 hasLocation W16255910314 @default.

• next