Content area

Abstract

An interesting problem arises when describing the frequency of losses in a given time period due to the fact that the data collection procedure may not distinguish subpopulations of risk sources. It consists of devising methods to determine the appropriate model for the frequency of losses due to each source of risk. When considering frequency models of the type (a, b, 0) there are several possible ways to disentangle a mixture of distributions. Here we present an application of the expectation-maximization algorithm and the k -means technique to provide a solution to the problem when the number of sources of risk is known.

Details

Title
Disentangling frequency models
Author
Gomes, Erika; Gzyl, Henryk
Pages
3-21
Publication year
2014
Publication date
Summer 2014
Publisher
Incisive Media Limited
ISSN
17446740
e-ISSN
17552710
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
1627699080
Copyright
Copyright Incisive Media Plc Summer 2014