Sequential change detection and hypothesis testing general non-i.i.d. stochastic models and asymptotically optimal rules / Alexander G. Tartakovsky, Moscow, Russia and Los Angeles, USA.
| Author/creator | Tartakovsky, Alexander |
| Format | Electronic |
| Publication Info | Boca Raton : CRC Press, Taylor & Francis Group, [2020] |
| Description | xix, 299 pages : illustrations ; 26 cm |
| Supplemental Content | Full text available from Taylor & Francis eBooks |
| Subjects |
| Contents | Sequential hypothesis testing in multiple data streams -- Sequential detection of changes : changepoint models, performance metrics and optimality criteria -- Bayesian quickest change detection in a single population -- Nearly optimal pointwise and minimax change detection in a single population -- Change detection rules optimal for the maximal detection probability criterion -- Quickest change detection in multiple streams -- Joint changepoint detection and identification -- Applications. |
| Abstract | "Statistical methods for sequential hypothesis testing and changepoint detection have applications across many fields. This book presents an overview of methodology in these related areas, providing a synthesis of research from the last few decades"-- Provided by publisher. |
| Bibliography note | Includes bibliographical references (pages 285-296) and index. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Genre/form | Electronic books. |
| LCCN | 2019040283 |
| ISBN | 9781498757584 (hardback) |
| ISBN | (ebook) |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | Access Content Online | ✔ Available |