Journal of Operational Risk
ISSN:
1744-6740 (print)
1755-2710 (online)
Editor-in-chief: Marcelo Cruz
Abstract
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 the authors 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.
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. Printing this content is for the sole use of the Authorised User (named subscriber), as outlined in our terms and conditions - https://www.infopro-insight.com/terms-conditions/insight-subscriptions/
If you would like to purchase additional rights please email info@risk.net
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. Copying this content is for the sole use of the Authorised User (named subscriber), as outlined in our terms and conditions - https://www.infopro-insight.com/terms-conditions/insight-subscriptions/
If you would like to purchase additional rights please email info@risk.net