Statistical Modeling for Degradation Data

Ding-Geng (Din) Chen

ISBN 10: 9811051933 / ISBN 13: 9789811051937

Edité par Springer Nature Singapore, Springer Nature Singapore, 2017

A propos de cet article

Druck auf Anfrage Neuware - Printed after ordering - 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.

N° de réf. du vendeur 9789811051937

Détails bibliographiques

• Titre: Statistical Modeling for Degradation Data
• Éditeur: Springer Nature Singapore, Springer Nature Singapore
• Date de parution: 2017
• Langue: anglais
• ISBN à 10 chiffres: 9811051933
• ISBN à 13 chiffres: 9789811051937
• Reliure: Buch
• État de l'article: Neu

A propos de ce titre

Synopsis

All authors are experts engaged in statistical modeling in degradation data analysis
Timely discussions of and presentations on methodological developments and real-world applications
Data and computer programs will be made publicly available, allowing readers to replicate the model development
Presents new, high-impact methods that are readily adoptable and extendable

À propos de l?auteur

Professor Chen is a fellow of the American Statistical Association and currently the Wallace Kuralt distinguished professor at the University of North Carolina at Chapel Hill, USA, and an extraordinary professor at University of Pretoria, South Africa. He was a professor at the University of Rochester and the Karl E. Peace endowed eminent scholar chair in biostatistics at Georgia Southern University. He is also a senior consultant for biopharmaceuticals and government agencies with extensive expertise in clinical trial biostatistics and public health statistics. Professor Chen has written more than 150 referred publications and co-authored/co-edited twelve books on clinical trial methodology with R and SAS, meta-analysis using R, advanced statistical causal-inference modeling, Monte-Carlo simulations, advanced public health statistics and statistical models in data science.

Professor Lio is a professor at the University of South Dakota. He has been invited nationally and internationally to give speeches on his research, and has produced more than 70 peer-reviewed professional publications in the areas of survival analysis, computational statistics and industrial statistics (including quality control, life test, degradation modeling, etc.)

Professor Ng is a professor at the Department of Statistical Science, Southern Methodist University, Dallas, Texas, USA. He is currently an Associate Editor of Communications in Statistics, Computational Statistics, Journal of Statistical Computation and Simulation, and Statistics and Probability Letters. Professor Ng has more than 100 peer-reviewed professional publications to his credit, and has co-authored and co-edited two books in the areas of nonparametric methods, ordered data analysis, reliability, censoring methodology, and statistical inference. Professor Ng is an elected member of the International Statistical Institute and an elected senior member of the Institute of Electrical and Electronics Engineers (IEEE).

Professor Tsai is a professor at the Department of Statistics at Tamkang University. His main research interests include quality control and reliability analysis. He previously served as a consultant for electronics companies and research institutes in Taiwan, and he has written more than 60 peer-reviewed professional publications in the areas of quality control and reliability applications.