Matches in SemOpenAlex for { <https://semopenalex.org/work/W1660951684> ?p ?o ?g. }
- W1660951684 endingPage "1940" @default.
- W1660951684 startingPage "1928" @default.
- W1660951684 abstract "In this paper, the third in a series illustrating the power of generalized linear models (GLMs) for the astronomical community, we elucidate the potential of the class of GLMs which handles count data. The size of a galaxy's globular cluster (GC) population (NGC) is a prolonged puzzle in the astronomical literature. It falls in the category of count data analysis, yet it is usually modelled as if it were a continuous response variable. We have developed a Bayesian negative binomial regression model to study the connection between NGC and the following galaxy properties: central black hole mass, dynamical bulge mass, bulge velocity dispersion and absolute visual magnitude. The methodology introduced herein naturally accounts for heteroscedasticity, intrinsic scatter, errors in measurements in both axes (either discrete or continuous) and allows modelling the population of GCs on their natural scale as a non-negative integer variable. Prediction intervals of 99 per cent around the trend for expected NGC comfortably envelope the data, notably including the Milky Way, which has hitherto been considered a problematic outlier. Finally, we demonstrate how random intercept models can incorporate information of each particular galaxy morphological type. Bayesian variable selection methodology allows for automatically identifying galaxy types with different productions of GCs, suggesting that on average S0 galaxies have a GC population 35 per cent smaller than other types with similar brightness." @default.
- W1660951684 created "2016-06-24" @default.
- W1660951684 creator A5000669585 @default.
- W1660951684 creator A5008195414 @default.
- W1660951684 creator A5018561836 @default.
- W1660951684 creator A5027375248 @default.
- W1660951684 creator A5033439062 @default.
- W1660951684 creator A5034547685 @default.
- W1660951684 creator A5038880723 @default.
- W1660951684 creator A5065617837 @default.
- W1660951684 date "2015-08-26" @default.
- W1660951684 modified "2023-10-03" @default.
- W1660951684 title "The overlooked potential of generalized linear models in astronomy – III. Bayesian negative binomial regression and globular cluster populations" @default.
- W1660951684 cites W1644145788 @default.
- W1660951684 cites W1973628995 @default.
- W1660951684 cites W1980878348 @default.
- W1660951684 cites W1982652137 @default.
- W1660951684 cites W2006796627 @default.
- W1660951684 cites W2012785637 @default.
- W1660951684 cites W2013479815 @default.
- W1660951684 cites W2021347741 @default.
- W1660951684 cites W2034221989 @default.
- W1660951684 cites W2045619533 @default.
- W1660951684 cites W2057765075 @default.
- W1660951684 cites W2074987412 @default.
- W1660951684 cites W2078805448 @default.
- W1660951684 cites W2089065774 @default.
- W1660951684 cites W2092193844 @default.
- W1660951684 cites W2102825905 @default.
- W1660951684 cites W2115490554 @default.
- W1660951684 cites W2126519315 @default.
- W1660951684 cites W2127137670 @default.
- W1660951684 cites W2129948640 @default.
- W1660951684 cites W2148534890 @default.
- W1660951684 cites W2149496379 @default.
- W1660951684 cites W2151702424 @default.
- W1660951684 cites W2169224160 @default.
- W1660951684 cites W2753666478 @default.
- W1660951684 cites W2801490189 @default.
- W1660951684 cites W3097989181 @default.
- W1660951684 cites W3100679294 @default.
- W1660951684 cites W3103401825 @default.
- W1660951684 cites W3104778445 @default.
- W1660951684 cites W3104928199 @default.
- W1660951684 cites W3105754910 @default.
- W1660951684 cites W3122676058 @default.
- W1660951684 cites W4247460398 @default.
- W1660951684 cites W618548231 @default.
- W1660951684 doi "https://doi.org/10.1093/mnras/stv1825" @default.
- W1660951684 hasPublicationYear "2015" @default.
- W1660951684 type Work @default.
- W1660951684 sameAs 1660951684 @default.
- W1660951684 citedByCount "21" @default.
- W1660951684 countsByYear W16609516842015 @default.
- W1660951684 countsByYear W16609516842016 @default.
- W1660951684 countsByYear W16609516842017 @default.
- W1660951684 countsByYear W16609516842018 @default.
- W1660951684 countsByYear W16609516842019 @default.
- W1660951684 countsByYear W16609516842021 @default.
- W1660951684 countsByYear W16609516842022 @default.
- W1660951684 countsByYear W16609516842023 @default.
- W1660951684 crossrefType "journal-article" @default.
- W1660951684 hasAuthorship W1660951684A5000669585 @default.
- W1660951684 hasAuthorship W1660951684A5008195414 @default.
- W1660951684 hasAuthorship W1660951684A5018561836 @default.
- W1660951684 hasAuthorship W1660951684A5027375248 @default.
- W1660951684 hasAuthorship W1660951684A5033439062 @default.
- W1660951684 hasAuthorship W1660951684A5034547685 @default.
- W1660951684 hasAuthorship W1660951684A5038880723 @default.
- W1660951684 hasAuthorship W1660951684A5065617837 @default.
- W1660951684 hasBestOaLocation W16609516841 @default.
- W1660951684 hasConcept C100906024 @default.
- W1660951684 hasConcept C105795698 @default.
- W1660951684 hasConcept C10767094 @default.
- W1660951684 hasConcept C113461152 @default.
- W1660951684 hasConcept C121332964 @default.
- W1660951684 hasConcept C1276947 @default.
- W1660951684 hasConcept C144024400 @default.
- W1660951684 hasConcept C149923435 @default.
- W1660951684 hasConcept C199335787 @default.
- W1660951684 hasConcept C2908647359 @default.
- W1660951684 hasConcept C33923547 @default.
- W1660951684 hasConcept C44870925 @default.
- W1660951684 hasConcept C555520305 @default.
- W1660951684 hasConcept C98444146 @default.
- W1660951684 hasConceptScore W1660951684C100906024 @default.
- W1660951684 hasConceptScore W1660951684C105795698 @default.
- W1660951684 hasConceptScore W1660951684C10767094 @default.
- W1660951684 hasConceptScore W1660951684C113461152 @default.
- W1660951684 hasConceptScore W1660951684C121332964 @default.
- W1660951684 hasConceptScore W1660951684C1276947 @default.
- W1660951684 hasConceptScore W1660951684C144024400 @default.
- W1660951684 hasConceptScore W1660951684C149923435 @default.
- W1660951684 hasConceptScore W1660951684C199335787 @default.
- W1660951684 hasConceptScore W1660951684C2908647359 @default.
- W1660951684 hasConceptScore W1660951684C33923547 @default.
- W1660951684 hasConceptScore W1660951684C44870925 @default.
- W1660951684 hasConceptScore W1660951684C555520305 @default.