Page 3 - Elements of Distribution Theory

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CUNY148/Severini-FM CUNY148/Severini June 8, 2005 17:55

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
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, conver-
gence in distribution, and the central limit theorem to more advanced
concepts such as exchangeability, models with a group structure, asymp-
totic approximations to integrals, orthogonal polynomials, and saddle-
point approximations. The emphasis is on topics useful in understand-
ing statistical methodology; thus, parametric statistical models and the
distribution theory associated with the normal distribution are covered
comprehensively.

Thomas A. Severini received his Ph.D. 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, Journal of the
American Statistical Association, and Journal of the Royal Statistical
Society.Heisa member of the Institute of Mathematical Statistics and
the American Statistical Association.

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