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:
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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
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.
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:
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.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 244 pp. Englisch. Codice articolo 9781447126348
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Discusses the use of modern statistical methods for the estimation of the performance measures of reliability systems that operate under different conditionsPresents some numerical or simulation methods as illustrative examples where computer-base. Codice articolo 11770505
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Taschenbuch. Condizione: Neu. Applied Nonparametric Statistics in Reliability | M. Luz Gámiz (u. a.) | Taschenbuch | Springer Series in Reliability Engineering | xiii | Englisch | 2014 | Springer | EAN 9781447126348 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Codice articolo 105058257
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 244 pp. Englisch. Codice articolo 9781447126348
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Taschenbuch. Condizione: Neu. 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. Codice articolo 9781447126348
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