TY  - DATA
AU  - Pham, Hoang.
TI  - Statistical Reliability Engineering: Methods, Models and Applications 
SN  - 9783030769048
U1  - 658.5 23
PY  - 2022///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Industrial Management
KW  - Security systems
KW  - Statistics 
KW  - Industrial engineering
KW  - Production engineering
KW  - Computers
KW  - Computer science-Mathematics
KW  - Mathematical statistics
KW  - Security Science and Technology
KW  - Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences
KW  - Industrial and Production Engineering
KW  - Hardware Performance and Reliability
KW  - Probability and Statistics in Computer Science
N1  - Probability, Statistics, and Reliability Concepts -- Distribution Functions and Its Applications -- Statistical Parameter Estimation -- System Reliability Modeling -- Order Statistics and Reliability Estimation -- Stochastic Processes -- Maintenance Modeling -- Software Reliability -- Statistical Machine Learning Methods and Its Applications
N2  - This book presents the state-of-the-art methodology and detailed analytical models and methods used to assess the reliability of complex systems and related applications in statistical reliability engineering. It is a textbook based mainly on the author's recent research and publications as well as experience of over 30 years in this field. The book covers a wide range of methods and models in reliability, and their applications, including: statistical methods and model selection for machine learning; models for maintenance and software reliability; statistical reliability estimation of complex systems; and statistical reliability analysis of k out of n systems, standby systems and repairable systems. Offering numerous examples and solved problems within each chapter, this comprehensive text provides an introduction to reliability engineering graduate students, a reference for data scientists and reliability engineers, and a thorough guide for researchers and instructors in the field
UR  - https://doi.org/10.1007/978-3-030-76904-8
ER  -