Presents the relevant results related to the Generalized Lambda Distribution, the Generalized Bootstrap, and Monte Carlo simulation. This work provides the tables, algorithms, and computer programs needed for fitting continuous probability distributions to data in a variety of circumstances - covering bivariate as well as univariate distributions.

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.