Statistical Modeling for Degradation Data

Business & Finance, Economics, Statistics, Nonfiction, Science & Nature, Mathematics
Cover of the book Statistical Modeling for Degradation Data by , Springer Singapore
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Author: ISBN: 9789811051944
Publisher: Springer Singapore Publication: August 31, 2017
Imprint: Springer Language: English
Author:
ISBN: 9789811051944
Publisher: Springer Singapore
Publication: August 31, 2017
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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