Life Distributions: Structure of Nonparametric, Semiparametric, and Parametric Families Contributor(s): Marshall, Albert W. (Author), Olkin, Ingram (Author) |
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ISBN: 0387203338 ISBN-13: 9780387203331 Publisher: Springer
Binding Type: Hardcover - See All Available Formats & Editions Published: July 2007 Annotation: 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. Click for more in this series: Springer Series in Statistics |
Additional Information |
BISAC Categories: - Mathematics | Probability & Statistics - General - Technology & Engineering | Industrial Engineering - Technology & Engineering | Quality Control |
Dewey: 519.24 |
LCCN: 2007925439 |
Series: Springer Series in Statistics |
Physical Information: 1.64" H x 6.72" W x 9.47" L (2.73 lbs) 785 pages |
Features: Bibliography, Illustrated, Index, Table of Contents |
Descriptions, Reviews, Etc. |
Publisher Description: 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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