For over 200 years, practitioners have been developing
parametric families of probability distributions for data analysis.
More recently, an active development of nonparametric and
semiparametric families has occurred. This book includes an
extensive discussion of a wide variety of distribution families
nonparametric, semiparametric and parametric some well known and
some not. An all-encompassing view is taken for the purpose of
identifying relationships, origins and structures of the various
families. A unified methodological approach for the introduction of
parameters into families is developed, and the properties that the
parameters imbue a distribution are clarified. These results
provide essential tools for intelligent choice of models for data
analysis. Many of the results given are new and have not previously
appeared in print. This book provides a comprehensive reference for
anyone working with nonnegative data."
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