Article ID: | iaor20161481 |
Volume: | 32 |
Issue: | 4 |
Start Page Number: | 1307 |
End Page Number: | 1319 |
Publication Date: | Jun 2016 |
Journal: | Quality and Reliability Engineering International |
Authors: | Chen Yong, Zhou Shiyu, Das Devashish, Sievenpiper Crispian |
Keywords: | datamining, computers: data-structure |
Multiple streams of binary data occur commonly in practice. In this paper, we propose a hierarchical statistical model to describe multi‐stream binary data that demonstrate over‐dispersion. In such a model, a group of binary streams in a multi‐stream dataset is modeled by a beta‐binominal hierarchical mixture distribution. Using this hierarchical model structure, a cumulative sum (CUSUM) chart based on the log‐likelihood ratio is developed to monitor all the data streams simultaneously. The performance of the CUSUM chart is investigated and compared to conventional monitoring schemes through numerical studies and a real‐world dataset. It is shown that the CUSUM method using the hierarchical model is effective and advantageous over the conventional methods.