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Elements of Distribution Theory (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 17) - Softcover
Synopsis
This detailed introduction to distribution theory is designed as a text for the probability portion of the first year statistical theory sequence for Master's and PhD students in statistics, biostatistics, and econometrics. The text uses no measure theory, requiring only a background in calculus and linear algebra. Topics 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 and orthogonal polynomials. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book.
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Book Description
Distribution theory consists of those areas of probability theory that are useful in understanding the development of statistical methodology, with the focus on the calculation and approximation of probabilities and moments. This detailed introduction uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Topics 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, orthogonal polynomials, and saddlepoint approximations.
About the Author
Thomas A. Severini received his PhD in Statistics from the University of Chicago. He is now a Professor of Statistics at Northwestern University. He has also written Likelihood Methods in Statistics. He has published extensively in statistical journals such as Biometrika, the Journal of the American Statistical Association and the Journal of the Royal Statistical Society. He is a member of the Institute of Mathematical Statistics and the American Statistical Association.
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- PublisherCambridge University Press
- Publication date2011
- ISBN 10 1107630738
- ISBN 13 9781107630734
- BindingPaperback
- LanguageEnglish
- Edition number1
- Number of pages528
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Elements of Distribution Theory (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 17)
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Paperback. Condition: new. Paperback. 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. This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics and researchers who use statistical methods. Backgrounds in calculus and linear algebra are important, and a course in elementary mathematical analysis useful, but not required. An appendix summarizes the mathematical definitions and results outlined. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781107630734
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