Generalized bivariate beta distributions involving Appell’s hypergeometric function of the second kind
ABSTRACT: Let X1, X2 and X3 be independent random variables, X1 and X2 having a confluent hypergeometric function kind 1 distribution with probability density function proportional to x νi−1 i 1F1(αi; βi; −xi), i = 1, 2, and X3 having a standard gamma distribution with shape parameter ν3. Define (Y1...
- Autores:
-
Orozco Castañeda, Johanna Marcela
Nagar, Daya Krishna
Gupta, Arjun Kumar
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2012
- Institución:
- Universidad de Antioquia
- Repositorio:
- Repositorio UdeA
- Idioma:
- eng
- OAI Identifier:
- oai:bibliotecadigital.udea.edu.co:10495/41790
- Acceso en línea:
- https://hdl.handle.net/10495/41790
- Palabra clave:
- Funciones beta
Functions, beta
Teoría de las distribuciones (análisis funcional)
Theory of distributions (Functional analysis)
Funciones hipergeométricas
Hypergeometric functions
Funciones gamma
Functions, gamma
Funciones de coulomb
Coulomb functions
Distribución de Gauss
Gauss distribution
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/2.5/co/
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Repositorio UdeA |
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| dc.title.spa.fl_str_mv |
Generalized bivariate beta distributions involving Appell’s hypergeometric function of the second kind |
| title |
Generalized bivariate beta distributions involving Appell’s hypergeometric function of the second kind |
| spellingShingle |
Generalized bivariate beta distributions involving Appell’s hypergeometric function of the second kind Funciones beta Functions, beta Teoría de las distribuciones (análisis funcional) Theory of distributions (Functional analysis) Funciones hipergeométricas Hypergeometric functions Funciones gamma Functions, gamma Funciones de coulomb Coulomb functions Distribución de Gauss Gauss distribution |
| title_short |
Generalized bivariate beta distributions involving Appell’s hypergeometric function of the second kind |
| title_full |
Generalized bivariate beta distributions involving Appell’s hypergeometric function of the second kind |
| title_fullStr |
Generalized bivariate beta distributions involving Appell’s hypergeometric function of the second kind |
| title_full_unstemmed |
Generalized bivariate beta distributions involving Appell’s hypergeometric function of the second kind |
| title_sort |
Generalized bivariate beta distributions involving Appell’s hypergeometric function of the second kind |
| dc.creator.fl_str_mv |
Orozco Castañeda, Johanna Marcela Nagar, Daya Krishna Gupta, Arjun Kumar |
| dc.contributor.author.none.fl_str_mv |
Orozco Castañeda, Johanna Marcela Nagar, Daya Krishna Gupta, Arjun Kumar |
| dc.contributor.researchgroup.spa.fl_str_mv |
Análisis Multivariado |
| dc.subject.lemb.none.fl_str_mv |
Funciones beta Functions, beta Teoría de las distribuciones (análisis funcional) Theory of distributions (Functional analysis) Funciones hipergeométricas Hypergeometric functions Funciones gamma Functions, gamma Funciones de coulomb Coulomb functions Distribución de Gauss Gauss distribution |
| topic |
Funciones beta Functions, beta Teoría de las distribuciones (análisis funcional) Theory of distributions (Functional analysis) Funciones hipergeométricas Hypergeometric functions Funciones gamma Functions, gamma Funciones de coulomb Coulomb functions Distribución de Gauss Gauss distribution |
| description |
ABSTRACT: Let X1, X2 and X3 be independent random variables, X1 and X2 having a confluent hypergeometric function kind 1 distribution with probability density function proportional to x νi−1 i 1F1(αi; βi; −xi), i = 1, 2, and X3 having a standard gamma distribution with shape parameter ν3. Define (Y1, Y2) = (X1/X3, X2/X3) and (Z1, Z2) = (X1, X2)/(X1 + X2 + X3). In this article, we derive probability density functions of (Y1, Y2) and (Z1, Z2), and study their properties. We use the second hypergeometric function of Appell to express these density functions. |
| publishDate |
2012 |
| dc.date.issued.none.fl_str_mv |
2012 |
| dc.date.accessioned.none.fl_str_mv |
2024-09-05T00:56:55Z |
| dc.date.available.none.fl_str_mv |
2024-09-05T00:56:55Z |
| dc.type.spa.fl_str_mv |
Artículo de investigación |
| dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
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https://purl.org/redcol/resource_type/ART |
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http://purl.org/coar/version/c_970fb48d4fbd8a85 |
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info:eu-repo/semantics/article |
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info:eu-repo/semantics/publishedVersion |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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publishedVersion |
| dc.identifier.issn.none.fl_str_mv |
0898-1221 |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/10495/41790 |
| dc.identifier.doi.none.fl_str_mv |
10.1016/j.camwa.2012.06.006 |
| dc.identifier.eissn.none.fl_str_mv |
1873-7668 |
| identifier_str_mv |
0898-1221 10.1016/j.camwa.2012.06.006 1873-7668 |
| url |
https://hdl.handle.net/10495/41790 |
| dc.language.iso.spa.fl_str_mv |
eng |
| language |
eng |
| dc.relation.ispartofjournalabbrev.spa.fl_str_mv |
Comput. Math. Appl. |
| dc.relation.citationendpage.spa.fl_str_mv |
2519 |
| dc.relation.citationissue.spa.fl_str_mv |
8 |
| dc.relation.citationstartpage.spa.fl_str_mv |
2507 |
| dc.relation.citationvolume.spa.fl_str_mv |
64 |
| dc.relation.ispartofjournal.spa.fl_str_mv |
Computers and Mathematics with Applications |
| dc.rights.uri.*.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/2.5/co/ |
| dc.rights.uri.spa.fl_str_mv |
https://creativecommons.org/licenses/by-nc-nd/4.0/ |
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info:eu-repo/semantics/openAccess |
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http://purl.org/coar/access_right/c_abf2 |
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openAccess |
| dc.format.extent.spa.fl_str_mv |
13 páginas |
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application/pdf |
| dc.publisher.spa.fl_str_mv |
Pergamon Press Elsevier |
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Nueva York, Estados Unidos |
| institution |
Universidad de Antioquia |
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Orozco Castañeda, Johanna MarcelaNagar, Daya KrishnaGupta, Arjun KumarAnálisis Multivariado2024-09-05T00:56:55Z2024-09-05T00:56:55Z20120898-1221https://hdl.handle.net/10495/4179010.1016/j.camwa.2012.06.0061873-7668ABSTRACT: Let X1, X2 and X3 be independent random variables, X1 and X2 having a confluent hypergeometric function kind 1 distribution with probability density function proportional to x νi−1 i 1F1(αi; βi; −xi), i = 1, 2, and X3 having a standard gamma distribution with shape parameter ν3. Define (Y1, Y2) = (X1/X3, X2/X3) and (Z1, Z2) = (X1, X2)/(X1 + X2 + X3). In this article, we derive probability density functions of (Y1, Y2) and (Z1, Z2), and study their properties. We use the second hypergeometric function of Appell to express these density functions.Universidad de Antioquia. Vicerrectoría de investigación. Comité para el Desarrollo de la Investigación - CODICOL000676913 páginasapplication/pdfengPergamon PressElsevierNueva York, Estados Unidoshttp://creativecommons.org/licenses/by-nc-nd/2.5/co/https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Generalized bivariate beta distributions involving Appell’s hypergeometric function of the second kindArtículo de investigaciónhttp://purl.org/coar/resource_type/c_2df8fbb1https://purl.org/redcol/resource_type/ARThttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionFunciones betaFunctions, betaTeoría de las distribuciones (análisis funcional)Theory of distributions (Functional analysis)Funciones hipergeométricasHypergeometric functionsFunciones gammaFunctions, gammaFunciones de coulombCoulomb functionsDistribución de GaussGauss distributionComput. Math. Appl.25198250764Computers and Mathematics with ApplicationsCODI IN550CERoR:03bp5hc83PublicationLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://bibliotecadigital.udea.edu.co/bitstreams/a86144bc-d5fe-46fa-88b3-2fbf3b629c54/download8a4605be74aa9ea9d79846c1fba20a33MD52falseAnonymousREADORIGINALOrozcoJohanna_2012_ GeneralizedBivariateBeta.pdfOrozcoJohanna_2012_ GeneralizedBivariateBeta.pdfArtículo de investigaciónapplication/pdf332407https://bibliotecadigital.udea.edu.co/bitstreams/56f5b0e1-ddf2-431a-b555-a8cd8bb0de52/downloada044029436892a7c3b812ef4c16ef325MD51trueAnonymousREADTEXTOrozcoJohanna_2012_ GeneralizedBivariateBeta.pdf.txtOrozcoJohanna_2012_ GeneralizedBivariateBeta.pdf.txtExtracted texttext/plain44887https://bibliotecadigital.udea.edu.co/bitstreams/b7cc8c5b-ed0a-4d94-80a8-0b5931b98285/download329b4e1541e65bac26a9ed626ac3fba6MD57falseAnonymousREADTHUMBNAILOrozcoJohanna_2012_ GeneralizedBivariateBeta.pdf.jpgOrozcoJohanna_2012_ GeneralizedBivariateBeta.pdf.jpgGenerated Thumbnailimage/jpeg13263https://bibliotecadigital.udea.edu.co/bitstreams/4a25f2d2-56d3-40b1-b305-eb8655f98a4b/downloadba654a1909769ce6c666725f50e3913fMD58falseAnonymousREAD10495/41790oai:bibliotecadigital.udea.edu.co:10495/417902025-03-26 17:08:21.149http://creativecommons.org/licenses/by-nc-nd/2.5/co/open.accesshttps://bibliotecadigital.udea.edu.coRepositorio Institucional de la Universidad de Antioquiaaplicacionbibliotecadigitalbiblioteca@udea.edu.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 |