Multivariate Reduced-Rank Regression: Theory and Applications
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
New York, NY
Springer New York
1998
|
| Schriftenreihe: | Lecture Notes in Statistics
136 |
| Schlagwörter: | |
| Links: | https://doi.org/10.1007/978-1-4757-2853-8 |
| Beschreibung: | In the area of multivariate analysis, there are two broad themes that have emerged over time. The analysis typically involves exploring the variations in a set of interrelated variables or investigating the simultaneous relation ships between two or more sets of variables. In either case, the themes involve explicit modeling of the relationships or dimension-reduction of the sets of variables. The multivariate regression methodology and its variants are the preferred tools for the parametric modeling and descriptive tools such as principal components or canonical correlations are the tools used for addressing the dimension-reduction issues. Both act as complementary to each other and data analysts typically want to make use of these tools for a thorough analysis of multivariate data. A technique that combines the two broad themes in a natural fashion is the method of reduced-rank regres sion. This method starts with the classical multivariate regression model framework but recognizes the possibility for the reduction in the number of parameters through a restrietion on the rank of the regression coefficient matrix. This feature is attractive because regression methods, whether they are in the context of a single response variable or in the context of several response variables, are popular statistical tools. The technique of reduced rank regression and its encompassing features are the primary focus of this book. The book develops the method of reduced-rank regression starting from the classical multivariate linear regression model |
| Umfang: | 1 Online-Ressource (XIII, 258 p) |
| ISBN: | 9781475728538 9780387986012 |
| ISSN: | 0930-0325 |
| DOI: | 10.1007/978-1-4757-2853-8 |
Internformat
MARC
| LEADER | 00000nam a2200000zcb4500 | ||
|---|---|---|---|
| 001 | BV042421391 | ||
| 003 | DE-604 | ||
| 005 | 00000000000000.0 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 150317s1998 xx o|||| 00||| eng d | ||
| 020 | |a 9781475728538 |c Online |9 978-1-4757-2853-8 | ||
| 020 | |a 9780387986012 |c Print |9 978-0-387-98601-2 | ||
| 024 | 7 | |a 10.1007/978-1-4757-2853-8 |2 doi | |
| 035 | |a (OCoLC)1184490137 | ||
| 035 | |a (DE-599)BVBBV042421391 | ||
| 040 | |a DE-604 |b ger |e aacr | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-384 |a DE-703 |a DE-91 |a DE-634 | ||
| 082 | 0 | |a 519.5 |2 23 | |
| 084 | |a MAT 000 |2 stub | ||
| 100 | 1 | |a Reinsel, Gregory C. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Multivariate Reduced-Rank Regression |b Theory and Applications |c by Gregory C. Reinsel, Raja P. Velu |
| 264 | 1 | |a New York, NY |b Springer New York |c 1998 | |
| 300 | |a 1 Online-Ressource (XIII, 258 p) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 0 | |a Lecture Notes in Statistics |v 136 |x 0930-0325 | |
| 500 | |a In the area of multivariate analysis, there are two broad themes that have emerged over time. The analysis typically involves exploring the variations in a set of interrelated variables or investigating the simultaneous relation ships between two or more sets of variables. In either case, the themes involve explicit modeling of the relationships or dimension-reduction of the sets of variables. The multivariate regression methodology and its variants are the preferred tools for the parametric modeling and descriptive tools such as principal components or canonical correlations are the tools used for addressing the dimension-reduction issues. Both act as complementary to each other and data analysts typically want to make use of these tools for a thorough analysis of multivariate data. A technique that combines the two broad themes in a natural fashion is the method of reduced-rank regres sion. This method starts with the classical multivariate regression model framework but recognizes the possibility for the reduction in the number of parameters through a restrietion on the rank of the regression coefficient matrix. This feature is attractive because regression methods, whether they are in the context of a single response variable or in the context of several response variables, are popular statistical tools. The technique of reduced rank regression and its encompassing features are the primary focus of this book. The book develops the method of reduced-rank regression starting from the classical multivariate linear regression model | ||
| 650 | 4 | |a Statistics | |
| 650 | 4 | |a Statistics, general | |
| 650 | 4 | |a Statistik | |
| 650 | 0 | 7 | |a Multivariate Analyse |0 (DE-588)4040708-1 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Regressionsmodell |0 (DE-588)4127980-3 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Reduzierter Rang |0 (DE-588)4388839-2 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Regressionsmodell |0 (DE-588)4127980-3 |D s |
| 689 | 0 | 1 | |a Reduzierter Rang |0 (DE-588)4388839-2 |D s |
| 689 | 0 | 2 | |a Multivariate Analyse |0 (DE-588)4040708-1 |D s |
| 689 | 0 | |8 1\p |5 DE-604 | |
| 700 | 1 | |a Velu, Raja P. |e Sonstige |4 oth | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-1-4757-2853-8 |x Verlag |3 Volltext |
| 912 | |a ZDB-2-SMA | ||
| 912 | |a ZDB-2-BAE | ||
| 940 | 1 | |q ZDB-2-SMA_Archive | |
| 883 | 1 | |8 1\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-027856808 | |
Datensatz im Suchindex
| DE-BY-TUM_katkey | 2068400 |
|---|---|
| _version_ | 1821931218673860609 |
| any_adam_object | |
| author | Reinsel, Gregory C. |
| author_facet | Reinsel, Gregory C. |
| author_role | aut |
| author_sort | Reinsel, Gregory C. |
| author_variant | g c r gc gcr |
| building | Verbundindex |
| bvnumber | BV042421391 |
| classification_tum | MAT 000 |
| collection | ZDB-2-SMA ZDB-2-BAE |
| ctrlnum | (OCoLC)1184490137 (DE-599)BVBBV042421391 |
| dewey-full | 519.5 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5 |
| dewey-search | 519.5 |
| dewey-sort | 3519.5 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| doi_str_mv | 10.1007/978-1-4757-2853-8 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03407nam a2200517zcb4500</leader><controlfield tag="001">BV042421391</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">150317s1998 xx o|||| 00||| eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781475728538</subfield><subfield code="c">Online</subfield><subfield code="9">978-1-4757-2853-8</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9780387986012</subfield><subfield code="c">Print</subfield><subfield code="9">978-0-387-98601-2</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/978-1-4757-2853-8</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1184490137</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV042421391</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">aacr</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-384</subfield><subfield code="a">DE-703</subfield><subfield code="a">DE-91</subfield><subfield code="a">DE-634</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">519.5</subfield><subfield code="2">23</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">MAT 000</subfield><subfield code="2">stub</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Reinsel, Gregory C.</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Multivariate Reduced-Rank Regression</subfield><subfield code="b">Theory and Applications</subfield><subfield code="c">by Gregory C. Reinsel, Raja P. Velu</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">New York, NY</subfield><subfield code="b">Springer New York</subfield><subfield code="c">1998</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (XIII, 258 p)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Lecture Notes in Statistics</subfield><subfield code="v">136</subfield><subfield code="x">0930-0325</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">In the area of multivariate analysis, there are two broad themes that have emerged over time. The analysis typically involves exploring the variations in a set of interrelated variables or investigating the simultaneous relation ships between two or more sets of variables. In either case, the themes involve explicit modeling of the relationships or dimension-reduction of the sets of variables. The multivariate regression methodology and its variants are the preferred tools for the parametric modeling and descriptive tools such as principal components or canonical correlations are the tools used for addressing the dimension-reduction issues. Both act as complementary to each other and data analysts typically want to make use of these tools for a thorough analysis of multivariate data. A technique that combines the two broad themes in a natural fashion is the method of reduced-rank regres sion. This method starts with the classical multivariate regression model framework but recognizes the possibility for the reduction in the number of parameters through a restrietion on the rank of the regression coefficient matrix. This feature is attractive because regression methods, whether they are in the context of a single response variable or in the context of several response variables, are popular statistical tools. The technique of reduced rank regression and its encompassing features are the primary focus of this book. The book develops the method of reduced-rank regression starting from the classical multivariate linear regression model</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Statistics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Statistics, general</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Statistik</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Multivariate Analyse</subfield><subfield code="0">(DE-588)4040708-1</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Regressionsmodell</subfield><subfield code="0">(DE-588)4127980-3</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Reduzierter Rang</subfield><subfield code="0">(DE-588)4388839-2</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Regressionsmodell</subfield><subfield code="0">(DE-588)4127980-3</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><subfield code="a">Reduzierter Rang</subfield><subfield code="0">(DE-588)4388839-2</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="2"><subfield code="a">Multivariate Analyse</subfield><subfield code="0">(DE-588)4040708-1</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="8">1\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Velu, Raja P.</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1007/978-1-4757-2853-8</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-2-SMA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-2-BAE</subfield></datafield><datafield tag="940" ind1="1" ind2=" "><subfield code="q">ZDB-2-SMA_Archive</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">1\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-027856808</subfield></datafield></record></collection> |
| id | DE-604.BV042421391 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-20T17:10:44Z |
| institution | BVB |
| isbn | 9781475728538 9780387986012 |
| issn | 0930-0325 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027856808 |
| oclc_num | 1184490137 |
| open_access_boolean | |
| owner | DE-384 DE-703 DE-91 DE-BY-TUM DE-634 |
| owner_facet | DE-384 DE-703 DE-91 DE-BY-TUM DE-634 |
| physical | 1 Online-Ressource (XIII, 258 p) |
| psigel | ZDB-2-SMA ZDB-2-BAE ZDB-2-SMA_Archive |
| publishDate | 1998 |
| publishDateSearch | 1998 |
| publishDateSort | 1998 |
| publisher | Springer New York |
| record_format | marc |
| series2 | Lecture Notes in Statistics |
| spellingShingle | Reinsel, Gregory C. Multivariate Reduced-Rank Regression Theory and Applications Statistics Statistics, general Statistik Multivariate Analyse (DE-588)4040708-1 gnd Regressionsmodell (DE-588)4127980-3 gnd Reduzierter Rang (DE-588)4388839-2 gnd |
| subject_GND | (DE-588)4040708-1 (DE-588)4127980-3 (DE-588)4388839-2 |
| title | Multivariate Reduced-Rank Regression Theory and Applications |
| title_auth | Multivariate Reduced-Rank Regression Theory and Applications |
| title_exact_search | Multivariate Reduced-Rank Regression Theory and Applications |
| title_full | Multivariate Reduced-Rank Regression Theory and Applications by Gregory C. Reinsel, Raja P. Velu |
| title_fullStr | Multivariate Reduced-Rank Regression Theory and Applications by Gregory C. Reinsel, Raja P. Velu |
| title_full_unstemmed | Multivariate Reduced-Rank Regression Theory and Applications by Gregory C. Reinsel, Raja P. Velu |
| title_short | Multivariate Reduced-Rank Regression |
| title_sort | multivariate reduced rank regression theory and applications |
| title_sub | Theory and Applications |
| topic | Statistics Statistics, general Statistik Multivariate Analyse (DE-588)4040708-1 gnd Regressionsmodell (DE-588)4127980-3 gnd Reduzierter Rang (DE-588)4388839-2 gnd |
| topic_facet | Statistics Statistics, general Statistik Multivariate Analyse Regressionsmodell Reduzierter Rang |
| url | https://doi.org/10.1007/978-1-4757-2853-8 |
| work_keys_str_mv | AT reinselgregoryc multivariatereducedrankregressiontheoryandapplications AT velurajap multivariatereducedrankregressiontheoryandapplications |