Monitoring plays a key role in today's business environment, as large volumes of data are collected and processed on a regular basis. Ability to detect onset of new data regimes and patterns quickly is considered an important competitive advantage. Of special importance is the area of monitoring product reliability, where timely detection of unfavorable trends typically offers considerable opportunities of cost avoidance. We will discuss detection systems for reliability issues built by combining Monte-Carlo techniques with modern statistical methods rooted in the theory of Sequential Analysis, Change-point theory and Likelihood Ratio tests. We will illustrate applications of these methods in computer industry. © Springer-Verlag Berlin Heidelberg 2010.
CITATION STYLE
Yashchin, E. (2010). Computational and Monte-Carlo aspects of systems for monitoring reliability data. In Proceedings of COMPSTAT 2010 - 19th International Conference on Computational Statistics, Keynote, Invited and Contributed Papers (pp. 253–262). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-7908-2604-3_23
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