Although the study of statistical modelling has made great strides in recent years, the number and variety of distributions to choose from continue to create problems. . Focusing on techniques used successfully across many fields, Fitting Statistical Distributions presents all of the relevant results related to the Generalized Lambda Distribution, the Generalized Bootstrap, and Monte Carlo simulation. It provides the tables, algorithms, and computer programs needed for fitting continuous probability distributions to data in a wide variety of circumstances-covering bivariate as well as univariate distributions, and including situations where moments do not exist.
Although the study of statistical modelling has made great strides in recent years, the number and variety of distributions to choose from continue to create problems. . Focusing on techniques used successfully across many fields, Fitting Statistical Distributions presents all of the relevant results related to the Generalized Lambda Distribution, the Generalized Bootstrap, and Monte Carlo simulation. It provides the tables, algorithms, and computer programs needed for fitting continuous probability distributions to data in a wide variety of circumstances-covering bivariate as well as univariate distributions, and including situations where moments do not exist.
A new edition of the trusted guide on commonly used statistical distributions Fully updated to reflect the latest developments on the topic, Statistical Distributions, Fourth Edition continues to...
Over the last decade, statisticians have developed new statistical tools in the field of spatial point processes. At the same time, observational efforts have yielded a huge amount of new...
Designed as an introduction to statistical distribution theory.
* Includes a first chapter on basic notations and definitions that are essential to working with distributions.
* Remaining chapters...
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