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Handbook of Fitting Statistical Distributions with R Hardcover – October 1, 2010

ISBN-13: 000-1584887117 ISBN-10: 1584887117 Edition: Har/Com

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Editorial Reviews


"Zaven Karian and Edward Dudewicz, major authorities on the GLD, along with numerous colleagues have authored the most comprehensive reference on the theoretical and applied aspects of the GLD in conjunction with numerous ancillary topics. The Handbook is an exciting benchmark in the four-decade history of the GLD and outstanding anchor for state-of-the-practice. … Is the book recommended? Yes. The Handbook is a milestone on the GLD that should be embraced and have residence on the shelves of many practitioners, including myself. The typeset source code and included CD-ROM of software are valuable. The Handbook provides extensive real-world examples by the authors and numerous contributors pertaining to distributional analysis requiring the flexibility of the GLD. Therefore, the Handbook is also recommended for advanced data analysts."
The American Statistician, May 2014

"… reading through this book is certainly an enlightening experience—many different aspects of GLD modeling are shown and motivated (including the interesting potential for GLD mixture use in chromatographic spectra modelling). Interesting and idea-rich presentations of much more general approaches appear in various chapters …"
ISCB News, June 2012

About the Author

Zaven A. Karian holds the Benjamin Barney Chair of Mathematics and is a professor of mathematics and computer science at Denison University in Granville, Ohio. For over thirty-five years, Dr. Karian has been active as an instructor, researcher, and consultant in mathematics, computer science, statistics, and simulation. He has taught many workshops and short courses at various educational institutions, conferences, and professional societies.

Edward J. Dudewicz is a professor of mathematics at Syracuse University in New York. With more than four decades of experience, Dr. Dudewicz is internationally recognized for his solution of the heteroscedastic selection problem, his work on fitting statistical distributions, his development of the multivariate heteroscedastic method, and his solution of the Behrens–Fisher problem.

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