Non-central complex matrix-variate beta distribution
ABSTRACT: Let ~ ( ) , , , Xi CWm ni ∑ Θi where diag( ) , 0, , 0 , Θi = θi 2 … i = 1, 2. In this article, the distribution of ( ) , 1 1 −1 − = H U T X T where X1 + X2 H = TT and T is a complex lower triangular matrix with positive diagonal elements has been derived. The distribution of U is a noncent...
- Autores:
-
Nagar, Daya Krishna
Bedoya, Elizabeth
Lubin Arias, Elkin
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2004
- Institución:
- Universidad de Antioquia
- Repositorio:
- Repositorio UdeA
- Idioma:
- eng
- OAI Identifier:
- oai:bibliotecadigital.udea.edu.co:10495/30860
- Acceso en línea:
- https://hdl.handle.net/10495/30860
- Palabra clave:
- Matrices (matemáticas)
Matrices
Teoría de las distribuciones (análisis funcional)
Theory of distributions (Functional analysis)
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/2.5/co/
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Non-central complex matrix-variate beta distribution |
| title |
Non-central complex matrix-variate beta distribution |
| spellingShingle |
Non-central complex matrix-variate beta distribution Matrices (matemáticas) Matrices Teoría de las distribuciones (análisis funcional) Theory of distributions (Functional analysis) |
| title_short |
Non-central complex matrix-variate beta distribution |
| title_full |
Non-central complex matrix-variate beta distribution |
| title_fullStr |
Non-central complex matrix-variate beta distribution |
| title_full_unstemmed |
Non-central complex matrix-variate beta distribution |
| title_sort |
Non-central complex matrix-variate beta distribution |
| dc.creator.fl_str_mv |
Nagar, Daya Krishna Bedoya, Elizabeth Lubin Arias, Elkin |
| dc.contributor.author.none.fl_str_mv |
Nagar, Daya Krishna Bedoya, Elizabeth Lubin Arias, Elkin |
| dc.contributor.researchgroup.spa.fl_str_mv |
Análisis Multivariado |
| dc.subject.lemb.none.fl_str_mv |
Matrices (matemáticas) Matrices Teoría de las distribuciones (análisis funcional) Theory of distributions (Functional analysis) |
| topic |
Matrices (matemáticas) Matrices Teoría de las distribuciones (análisis funcional) Theory of distributions (Functional analysis) |
| description |
ABSTRACT: Let ~ ( ) , , , Xi CWm ni ∑ Θi where diag( ) , 0, , 0 , Θi = θi 2 … i = 1, 2. In this article, the distribution of ( ) , 1 1 −1 − = H U T X T where X1 + X2 H = TT and T is a complex lower triangular matrix with positive diagonal elements has been derived. The distribution of U is a noncentral complex matrix-variate beta distribution. Several properties of this distribution have also been studied. |
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2004 |
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2004 |
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2022-09-25T15:46:52Z |
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2022-09-25T15:46:52Z |
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Artículo de investigación |
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Nagar, Daya & Bedoya, Elizabeth & Arias, Elkin. (2004). Non-central complex matrix-variate beta distribution. Advances and Applications in Statistics. 4. 287-302 |
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0972-3617 |
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https://hdl.handle.net/10495/30860 |
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Nagar, Daya & Bedoya, Elizabeth & Arias, Elkin. (2004). Non-central complex matrix-variate beta distribution. Advances and Applications in Statistics. 4. 287-302 0972-3617 |
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https://hdl.handle.net/10495/30860 |
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eng |
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eng |
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Advances and Applications in Statistics |
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Nagar, Daya KrishnaBedoya, ElizabethLubin Arias, ElkinAnálisis Multivariado2022-09-25T15:46:52Z2022-09-25T15:46:52Z2004Nagar, Daya & Bedoya, Elizabeth & Arias, Elkin. (2004). Non-central complex matrix-variate beta distribution. Advances and Applications in Statistics. 4. 287-3020972-3617https://hdl.handle.net/10495/30860ABSTRACT: Let ~ ( ) , , , Xi CWm ni ∑ Θi where diag( ) , 0, , 0 , Θi = θi 2 … i = 1, 2. In this article, the distribution of ( ) , 1 1 −1 − = H U T X T where X1 + X2 H = TT and T is a complex lower triangular matrix with positive diagonal elements has been derived. The distribution of U is a noncentral complex matrix-variate beta distribution. Several properties of this distribution have also been studied.COL000053216application/pdfengPushpa Publishing HouseIndiahttp://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_abf2Non-central complex matrix-variate beta distributionArtículo 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/publishedVersionMatrices (matemáticas)MatricesTeoría de las distribuciones (análisis funcional)Theory of distributions (Functional analysis)30232874Advances and Applications in StatisticsPublicationORIGINALNagarDaya_2004_NoncentralComplexMatrixvariateBeta.pdfNagarDaya_2004_NoncentralComplexMatrixvariateBeta.pdfArtículo de investigaciónapplication/pdf190625https://bibliotecadigital.udea.edu.co/bitstreams/c57fe7d4-198e-4625-941a-4498efa0fecc/downloade097d3d972adf95695dbc158b4da96bfMD51trueAnonymousREADCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8823https://bibliotecadigital.udea.edu.co/bitstreams/207a05b9-680d-480e-9b4e-a492303685e2/downloadb88b088d9957e670ce3b3fbe2eedbc13MD52falseAnonymousREADLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://bibliotecadigital.udea.edu.co/bitstreams/59bb6a85-3536-48a6-807d-b3d302dc9073/download8a4605be74aa9ea9d79846c1fba20a33MD53falseAnonymousREADTEXTNagarDaya_2004_NoncentralComplexMatrixvariateBeta.pdf.txtNagarDaya_2004_NoncentralComplexMatrixvariateBeta.pdf.txtExtracted texttext/plain25430https://bibliotecadigital.udea.edu.co/bitstreams/3cc68eaf-e7b8-4cdb-ac4f-d6018e8f9a8e/download2de3e91f4a6ac4a8a438ee26efc66f2dMD54falseAnonymousREADTHUMBNAILNagarDaya_2004_NoncentralComplexMatrixvariateBeta.pdf.jpgNagarDaya_2004_NoncentralComplexMatrixvariateBeta.pdf.jpgGenerated Thumbnailimage/jpeg8236https://bibliotecadigital.udea.edu.co/bitstreams/ada97ecb-4d82-48d1-8693-8e2475d4e4ee/download26256a56fa908677161dd1561d5d2adaMD55falseAnonymousREAD10495/30860oai:bibliotecadigital.udea.edu.co:10495/308602025-03-26 18:28:52.841http://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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 |