Elements of distribution theory:
This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important and a course in elementary mathematical analy...
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1. Verfasser: | |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Cambridge
Cambridge University Press
2005
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Schriftenreihe: | Cambridge series on statistical and probabilistic mathematics
17 |
Schlagworte: | |
Online-Zugang: | BSB01 FHN01 URL des Erstveröffentlichers |
Zusammenfassung: | This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important and a course in elementary mathematical analysis is useful, but not required. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Topics covered range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals, orthogonal polynomials and saddlepoint approximations. The emphasis is on topics useful in understanding statistical methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are covered comprehensively |
Beschreibung: | Title from publisher's bibliographic system (viewed on 05 Oct 2015) |
Beschreibung: | 1 online resource (xii, 515 pages) |
ISBN: | 9780511610547 |
DOI: | 10.1017/CBO9780511610547 |
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520 | |a This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important and a course in elementary mathematical analysis is useful, but not required. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Topics covered range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals, orthogonal polynomials and saddlepoint approximations. The emphasis is on topics useful in understanding statistical methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are covered comprehensively | ||
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Datensatz im Suchindex
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author | Severini, Thomas A. 1959- |
author_facet | Severini, Thomas A. 1959- |
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dewey-ones | 515 - Analysis |
dewey-raw | 515/.782 |
dewey-search | 515/.782 |
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dewey-tens | 510 - Mathematics |
discipline | Mathematik Wirtschaftswissenschaften |
doi_str_mv | 10.1017/CBO9780511610547 |
format | Electronic eBook |
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spelling | Severini, Thomas A. 1959- Verfasser aut Elements of distribution theory Thomas A. Severini Cambridge Cambridge University Press 2005 1 online resource (xii, 515 pages) txt rdacontent c rdamedia cr rdacarrier Cambridge series on statistical and probabilistic mathematics 17 Title from publisher's bibliographic system (viewed on 05 Oct 2015) This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important and a course in elementary mathematical analysis is useful, but not required. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Topics covered range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals, orthogonal polynomials and saddlepoint approximations. The emphasis is on topics useful in understanding statistical methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are covered comprehensively Distribution (Probability theory) Wahrscheinlichkeitsverteilung (DE-588)4121894-2 gnd rswk-swf 1\p (DE-588)4123623-3 Lehrbuch gnd-content Wahrscheinlichkeitsverteilung (DE-588)4121894-2 s 2\p DE-604 Erscheint auch als Druckausgabe 978-0-521-84472-7 Erscheint auch als Druckausgabe 978-1-107-63073-4 https://doi.org/10.1017/CBO9780511610547 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
spellingShingle | Severini, Thomas A. 1959- Elements of distribution theory Distribution (Probability theory) Wahrscheinlichkeitsverteilung (DE-588)4121894-2 gnd |
subject_GND | (DE-588)4121894-2 (DE-588)4123623-3 |
title | Elements of distribution theory |
title_auth | Elements of distribution theory |
title_exact_search | Elements of distribution theory |
title_full | Elements of distribution theory Thomas A. Severini |
title_fullStr | Elements of distribution theory Thomas A. Severini |
title_full_unstemmed | Elements of distribution theory Thomas A. Severini |
title_short | Elements of distribution theory |
title_sort | elements of distribution theory |
topic | Distribution (Probability theory) Wahrscheinlichkeitsverteilung (DE-588)4121894-2 gnd |
topic_facet | Distribution (Probability theory) Wahrscheinlichkeitsverteilung Lehrbuch |
url | https://doi.org/10.1017/CBO9780511610547 |
work_keys_str_mv | AT severinithomasa elementsofdistributiontheory |