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Monographs on Applied Probability and Statistics Finite Mixture Distributions

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Specifiche dell'oggetto

Condizione
Nuovo: Libro nuovo, intatto e non letto, in perfette condizioni, senza pagine mancanti o ...
ISBN-10
0412224208
ISBN
9780412224201

Informazioni su questo prodotto

Product Identifiers

Publisher
Springer
ISBN-10
0412224208
ISBN-13
9780412224201
eBay Product ID (ePID)
904716

Product Key Features

Number of Pages
Xii, 143 Pages
Publication Name
Finite Mixture Distributions
Language
English
Subject
Probability & Statistics / General, General, Chemistry / General
Publication Year
1981
Type
Textbook
Author
D. J. Hand, B. S. Everitt
Subject Area
Mathematics, Science
Series
Monographs on Statistics and Applied Probability Ser.
Format
Hardcover

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
80-041131
Dewey Edition
19
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
519.5/32
Synopsis
Finite mixture distributions arise in a variety of applications ranging from the length distribution of fish to the content of DNA in the nuclei of liver cells. The literature surrounding them is large and goes back to the end of the last century when Karl Pearson published his well-known paper on estimating the five parameters in a mixture of two normal distributions. In this text we attempt to review this literature and in addition indicate the practical details of fitting such distributions to sample data. Our hope is that the monograph will be useful to statisticians interested in mixture distributions and to re­ search workers in other areas applying such distributions to their data. We would like to express our gratitude to Mrs Bertha Lakey for typing the manuscript. Institute oj Psychiatry B. S. Everitt University of London D. l Hand 1980 CHAPTER I General introduction 1. 1 Introduction This monograph is concerned with statistical distributions which can be expressed as superpositions of (usually simpler) component distributions. Such superpositions are termed mixture distributions or compound distributions. For example, the distribution of height in a population of children might be expressed as follows: h(height) = fg(height: age)f(age)d age (1. 1) where g(height: age) is the conditional distribution of height on age, and/(age) is the age distribution of the children in the population., Finite mixture distributions arise in a variety of applications ranging from the length distribution of fish to the content of DNA in the nuclei of liver cells. The literature surrounding them is large and goes back to the end of the last century when Karl Pearson published his well-known paper on estimating the five parameters in a mixture of two normal distributions. In this text we attempt to review this literature and in addition indicate the practical details of fitting such distributions to sample data. Our hope is that the monograph will be useful to statisticians interested in mixture distributions and to re search workers in other areas applying such distributions to their data. We would like to express our gratitude to Mrs Bertha Lakey for typing the manuscript. Institute oj Psychiatry B. S. Everitt University of London D. l Hand 1980 CHAPTER I General introduction 1. 1 Introduction This monograph is concerned with statistical distributions which can be expressed as superpositions of (usually simpler) component distributions. Such superpositions are termed mixture distributions or compound distributions. For example, the distribution of height in a population of children might be expressed as follows: h(height) = fg(height: age)f(age)d age (1. 1) where g(height: age) is the conditional distribution of height on age, and/(age) is the age distribution of the children in the population."
LC Classification Number
Q1-390

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