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Statistical modeling for degradation data
This book focuses on the statistical aspects of the analysis of degradation data. In recent years, degradation data analysis has come to play an increasingly important role in different disciplines such as reliability, public health sciences, and finance. For example, information on products’ reliab...
Autores principales: | , , , |
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Lenguaje: | eng |
Publicado: |
Springer
2017
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1007/978-981-10-5194-4 http://cds.cern.ch/record/2282102 |
_version_ | 1780955624407826432 |
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author | Chen, Ding-Geng Lio, Yuhlong Ng, Hon Tsai, Tzong-Ru |
author_facet | Chen, Ding-Geng Lio, Yuhlong Ng, Hon Tsai, Tzong-Ru |
author_sort | Chen, Ding-Geng |
collection | CERN |
description | This book focuses on the statistical aspects of the analysis of degradation data. In recent years, degradation data analysis has come to play an increasingly important role in different disciplines such as reliability, public health sciences, and finance. For example, information on products’ reliability can be obtained by analyzing degradation data. In addition, statistical modeling and inference techniques have been developed on the basis of different degradation measures. The book brings together experts engaged in statistical modeling and inference, presenting and discussing important recent advances in degradation data analysis and related applications. The topics covered are timely and have considerable potential to impact both statistics and reliability engineering. |
id | cern-2282102 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2017 |
publisher | Springer |
record_format | invenio |
spelling | cern-22821022021-04-21T19:05:03Zdoi:10.1007/978-981-10-5194-4http://cds.cern.ch/record/2282102engChen, Ding-GengLio, YuhlongNg, HonTsai, Tzong-RuStatistical modeling for degradation dataMathematical Physics and MathematicsThis book focuses on the statistical aspects of the analysis of degradation data. In recent years, degradation data analysis has come to play an increasingly important role in different disciplines such as reliability, public health sciences, and finance. For example, information on products’ reliability can be obtained by analyzing degradation data. In addition, statistical modeling and inference techniques have been developed on the basis of different degradation measures. The book brings together experts engaged in statistical modeling and inference, presenting and discussing important recent advances in degradation data analysis and related applications. The topics covered are timely and have considerable potential to impact both statistics and reliability engineering.Springeroai:cds.cern.ch:22821022017 |
spellingShingle | Mathematical Physics and Mathematics Chen, Ding-Geng Lio, Yuhlong Ng, Hon Tsai, Tzong-Ru Statistical modeling for degradation data |
title | Statistical modeling for degradation data |
title_full | Statistical modeling for degradation data |
title_fullStr | Statistical modeling for degradation data |
title_full_unstemmed | Statistical modeling for degradation data |
title_short | Statistical modeling for degradation data |
title_sort | statistical modeling for degradation data |
topic | Mathematical Physics and Mathematics |
url | https://dx.doi.org/10.1007/978-981-10-5194-4 http://cds.cern.ch/record/2282102 |
work_keys_str_mv | AT chendinggeng statisticalmodelingfordegradationdata AT lioyuhlong statisticalmodelingfordegradationdata AT nghon statisticalmodelingfordegradationdata AT tsaitzongru statisticalmodelingfordegradationdata |