Constructing a multivariate distribution function with a vine copula: toward multivariate luminosity and mass functions

التفاصيل البيبلوغرافية
العنوان: Constructing a multivariate distribution function with a vine copula: toward multivariate luminosity and mass functions
المؤلفون: Takeuchi, Tsutomu T., Kono, Kai T.
سنة النشر: 2020
المجموعة: Astrophysics
مصطلحات موضوعية: Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
الوصف: The need for a method to construct multidimensional distribution function is increasing recently, in the era of huge multiwavelength surveys. We have proposed a systematic method to build a bivariate luminosity or mass function of galaxies by using a copula. It allows us to construct a distribution function when only its marginal distributions are known, and we have to estimate the dependence structure from data. A typical example is the situation that we have univariate luminosity functions at some wavelengths for a survey, but the joint distribution is unknown. Main limitation of the copula method is that it is not easy to extend a joint function to higher dimensions ($d > 2$), except some special cases like multidimensional Gaussian. Even if we find such a multivariate analytic function in some fortunate case, it would often be inflexible and impractical. In this work, we show a systematic method to extend the copula method to unlimitedly higher dimensions by a vine copula. This is based on the pair-copula decomposition of a general multivariate distribution. We show how the vine copula construction is flexible and extendable. We also present an example of the construction of an stellar mass--atomic gas--molecular gas 3-dimensional mass function. We demonstrate the maximum likelihood estimation of the best functional form for this function, as well as a proper model selection via vine copula.
Comment: 15 pages, 9 figures. Submitted to MNRAS on 7 May 2020, accepted for publication on 17 August 2020
نوع الوثيقة: Working Paper
DOI: 10.1093/mnras/staa2558
URL الوصول: http://arxiv.org/abs/2006.05668
رقم الانضمام: edsarx.2006.05668
قاعدة البيانات: arXiv
ResultId 1
Header edsarx
arXiv
edsarx.2006.05668
1008
3
Report
report
1007.68402099609
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&scope=site&db=edsarx&AN=edsarx.2006.05668&custid=s6537998&authtype=sso
FullText Array ( [Availability] => 0 )
Array ( [0] => Array ( [Url] => http://arxiv.org/abs/2006.05668 [Name] => EDS - Arxiv [Category] => fullText [Text] => View record in Arxiv [MouseOverText] => View record in Arxiv ) )
Items Array ( [Name] => Title [Label] => Title [Group] => Ti [Data] => Constructing a multivariate distribution function with a vine copula: toward multivariate luminosity and mass functions )
Array ( [Name] => Author [Label] => Authors [Group] => Au [Data] => <searchLink fieldCode="AR" term="%22Takeuchi%2C+Tsutomu+T%2E%22">Takeuchi, Tsutomu T.</searchLink><br /><searchLink fieldCode="AR" term="%22Kono%2C+Kai+T%2E%22">Kono, Kai T.</searchLink> )
Array ( [Name] => DatePubCY [Label] => Publication Year [Group] => Date [Data] => 2020 )
Array ( [Name] => Subset [Label] => Collection [Group] => HoldingsInfo [Data] => Astrophysics )
Array ( [Name] => Subject [Label] => Subject Terms [Group] => Su [Data] => <searchLink fieldCode="DE" term="%22Astrophysics+-+Astrophysics+of+Galaxies%22">Astrophysics - Astrophysics of Galaxies</searchLink><br /><searchLink fieldCode="DE" term="%22Astrophysics+-+Instrumentation+and+Methods+for+Astrophysics%22">Astrophysics - Instrumentation and Methods for Astrophysics</searchLink> )
Array ( [Name] => Abstract [Label] => Description [Group] => Ab [Data] => The need for a method to construct multidimensional distribution function is increasing recently, in the era of huge multiwavelength surveys. We have proposed a systematic method to build a bivariate luminosity or mass function of galaxies by using a copula. It allows us to construct a distribution function when only its marginal distributions are known, and we have to estimate the dependence structure from data. A typical example is the situation that we have univariate luminosity functions at some wavelengths for a survey, but the joint distribution is unknown. Main limitation of the copula method is that it is not easy to extend a joint function to higher dimensions ($d > 2$), except some special cases like multidimensional Gaussian. Even if we find such a multivariate analytic function in some fortunate case, it would often be inflexible and impractical. In this work, we show a systematic method to extend the copula method to unlimitedly higher dimensions by a vine copula. This is based on the pair-copula decomposition of a general multivariate distribution. We show how the vine copula construction is flexible and extendable. We also present an example of the construction of an stellar mass--atomic gas--molecular gas 3-dimensional mass function. We demonstrate the maximum likelihood estimation of the best functional form for this function, as well as a proper model selection via vine copula.<br />Comment: 15 pages, 9 figures. Submitted to MNRAS on 7 May 2020, accepted for publication on 17 August 2020 )
Array ( [Name] => TypeDocument [Label] => Document Type [Group] => TypDoc [Data] => Working Paper )
Array ( [Name] => DOI [Label] => DOI [Group] => ID [Data] => 10.1093/mnras/staa2558 )
Array ( [Name] => URL [Label] => Access URL [Group] => URL [Data] => <link linkTarget="URL" linkTerm="http://arxiv.org/abs/2006.05668" linkWindow="_blank">http://arxiv.org/abs/2006.05668</link> )
Array ( [Name] => AN [Label] => Accession Number [Group] => ID [Data] => edsarx.2006.05668 )
RecordInfo Array ( [BibEntity] => Array ( [Identifiers] => Array ( [0] => Array ( [Type] => doi [Value] => 10.1093/mnras/staa2558 ) ) [Subjects] => Array ( [0] => Array ( [SubjectFull] => Astrophysics - Astrophysics of Galaxies [Type] => general ) [1] => Array ( [SubjectFull] => Astrophysics - Instrumentation and Methods for Astrophysics [Type] => general ) ) [Titles] => Array ( [0] => Array ( [TitleFull] => Constructing a multivariate distribution function with a vine copula: toward multivariate luminosity and mass functions [Type] => main ) ) ) [BibRelationships] => Array ( [HasContributorRelationships] => Array ( [0] => Array ( [PersonEntity] => Array ( [Name] => Array ( [NameFull] => Takeuchi, Tsutomu T. ) ) ) [1] => Array ( [PersonEntity] => Array ( [Name] => Array ( [NameFull] => Kono, Kai T. ) ) ) ) [IsPartOfRelationships] => Array ( [0] => Array ( [BibEntity] => Array ( [Dates] => Array ( [0] => Array ( [D] => 10 [M] => 06 [Type] => published [Y] => 2020 ) ) ) ) ) ) )
IllustrationInfo