Elements of distribution theory / Thomas A. Severini.
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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| Online Access: |
Full Text (via Cambridge) |
|---|---|
| Main Author: | |
| Corporate Author: | |
| Other title: | Cambridge books online Mathematics. |
| Format: | eBook |
| Language: | English |
| Published: |
Cambridge :
Cambridge University Press,
2005.
|
| Series: | Cambridge series on statistical and probabilistic mathematics ;
17. |
| Subjects: |
MARC
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| 100 | 1 | |a Severini, Thomas A. | |
| 245 | 1 | 0 | |a Elements of distribution theory / |c Thomas A. Severini. |
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| 300 | |a 1 online resource (528 pages) | ||
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| 490 | 1 | |a Cambridge series on statistical and probabilistic mathematics ; |v no. 17 | |
| 504 | |a Includes bibliographical references (pages 503-505) and indexes. | ||
| 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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| 830 | 0 | |a Cambridge series on statistical and probabilistic mathematics ; |v 17. | |
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