With the development of new fitting methods, their increased use in applications, and improved computer languages, the fitting of statistical distributions to data has come a long way since the introduction of the generalized lambda distribution (GLD) in 1969. Handbook of Fitting Statistical Distributions with R presents the latest and best methods, algorithms, and computations for fitting distributions to data. It also provides in-depth coverage of cutting-edge applications. The book begins with commentary by three GLD pioneers: John S. Ramberg, Bruce Schmeiser, and Pandu R. Tadikamalla. These leaders of the field give their perspectives on the development of the GLD. The book then covers GLD methodology and Johnson, kappa, and response modeling methodology fitting systems. It also describes recent additions to GLD and generalized bootstrap methods as well as a new approach to goodness-of-fit assessment. The final group of chapters explores real-world applications in agriculture, reliability estimation, hurricanes/typhoons/cyclones, hail storms, water systems, insurance and inventory management, and materials science. The applications in these chapters complement others in the book that deal with competitive bidding, medicine, biology, meteorology, bioassays, economics, quality management, engineering, control, and planning. New results in the field have generated a rich array of methods for practitioners. Making sense of this extensive growth, this comprehensive and authoritative handbook improves your understanding of the methodology and applications of fitting statistical distributions. The accompanying CD-ROM includes the R programs used for many of the computations.

Strengthened by examples taken from the scientific literature, this handbook provides statisticians and researchers across the physical and social sciences with cutting-edge methods for fitting continuous probability distributions. It presents families with wide-ranging applicability, including Johnsona (TM)s system, kappa distribution, and generalized lambda distribution. By providing the necessary R programs, the book enables practitioners to implement the techniques using R computer code. To cover distribution method combinations not included in the booka (TM)s extensive tables, the authors delve into the application of computational algorithms and attendant approximation errors.

"... this is an enormously rich and useful handbook representing well the state of art in this area. ... This handbook should be available in any institutional library, and it will be more than useful to both theorists and applied scientists."-Zentralblatt MATH 1282 "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