The Expectation-Maximization (EM) algorithm is a broadly applicable approach to the iterative computation of maximum likelihood (ML) estimates, useful in a variety of incomplete-data problems. Maximum likelihood estimation and likelihood-based inference are of central importance in statistical...

Partial observability is a prominent feature of accounting fraud. Not only the act of committing fraud is not directly observable, but the detected frauds are often revealed to the public with substantial time delays. In this article, we specify an underlying fraud data generating process that...

The important role of finite mixture models in the statistical analysis of data is underscored by the ever-increasing rate at which articles on mixture applications appear in the statistical and general scientific literature. The aim of this article is to provide an up-to-date account of the...