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.