Applied Nonparametric Statistics in Reliability
Language: English
Published by Springer London, 2011
Series: Book 15 of 90 - Springer Series in Reliability Engineering
- Hardcover
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Druck auf Anfrage Neuware - Printed after ordering - Nonparametric statistics has probably become the leading methodology for researchers performing data analysis. It is nevertheless true that, whereas these methods have already proved highly effective in other applied areas of knowledge such as biostatistics or social sciences, nonparametric analyses in reliability currently form an interesting area of study that has not yet been fully explored.Applied Nonparametric Statistics in Reliability is focused on the use of modern statistical methods for the estimation of dependability measures of reliability systems that operate under different conditions. The scope of the book includes:smooth estimation of the reliability function and hazard rate of non-repairable systems;study of stochastic processes for modelling the time evolution of systems when imperfect repairs are performed;nonparametric analysis of discrete and continuous time semi-Markov processes;isotonic regression analysis of the structure function of a reliability system, andlifetime regression analysis.Besides the explanation of the mathematical background, several numerical computations or simulations are presented as illustrative examples. The corresponding computer-based methods have been implemented using R and MATLAB®. A concrete modelling scheme is chosen for each practical situation and, in consequence, a nonparametric inference procedure is conducted.Applied Nonparametric Statistics in Reliability will serve the practical needs of scientists (statisticians and engineers) working on applied reliability subjects.…
Seller Inventory # 9780857291172
- Title
- Applied Nonparametric Statistics in Reliability
- Author
- M Luz Gámiz
- Publisher
- Springer London
- Publication year
- 2011
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 0857291173
- ISBN 13
- 9780857291172
- Item weight
- 509 grams
- Dimensions
- 240x167x23 mm
- Series
- Book 15 of 90: Springer Series in Reliability Engineering
Nonparametric statistics has probably become the leading methodology for researchers performing data analysis. It is nevertheless true that, whereas these methods have already proved highly effective in other applied areas of knowledge such as biostatistics or social sciences, nonparametric analyses in reliability currently form an interesting area of study that has not yet been fully explored.
Applied Nonparametric Statistics in Reliability is focused on the use of modern statistical methods for the estimation of dependability measures of reliability systems that operate under different conditions. The scope of the book includes:
- smooth estimation of the reliability function and hazard rate of non-repairable systems;
- study of stochastic processes for modelling the time evolution of systems when imperfect repairs are performed;
- nonparametric analysis of discrete and continuous time semi-Markov processes;
- isotonic regression analysis of the structure function of a reliability system, and
- lifetime regression analysis.
Besides the explanation of the mathematical background, several numerical computations or simulations are presented as illustrative examples. The corresponding computer-based methods have been implemented using R and MATLAB®. A concrete modelling scheme is chosen for each practical situation and, in consequence, a nonparametric inference procedure is conducted.
Applied Nonparametric Statistics in Reliability will serve the practical needs of scientists (statisticians and engineers) working on applied reliability subjects.
"Synopsis" may belong to another edition of this title.
About the Author
M. Luz Gámiz is an associate professor in the Department of Statistics and Operational Research at the University of Granada, Granada, Spain.
K. B. Kulasekera is a professor and graduate program coordinator in the Department of Mathematical Sciences at Clemson University, Clemson, USA.
Nikolaos Limnios is a professor at the Université de Technologie de Compiègne, Compiègne, France.
Bo Henry Lindqvist is a professor of statistics in the Department of Mathematical Sciences at the Norwegian University of Science and Technology, Trondheim, Norway.
"About the title" may belong to another edition of this title.
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