Bayesian Reliability / Michael S. Hamada (2008)  

Público ISBD Título : Bayesian Reliability Tipo de documento: documento electrónico Autores: Michael S. Hamada ; SpringerLink (Online service) ; Alyson G. Wilson ; C. Shane Reese ; Harry F. Martz Editorial: New York, NY : Springer New York Fecha de publicación: 2008 Colección: Springer Series in Statistics, ISSN 0172-7397 Número de páginas: XVI, 436 p Il.: online resource ISBN/ISSN/DL: 978-0-387-77950-8 Idioma : Inglés (eng) Palabras clave: Mathematics  Probabilities  Statistics  Quality  control  Reliability  Industrial  safety  Probability  Theory  and  Stochastic  Processes  for  Engineering,  Physics,  Computer  Science,  Chemistry  Earth  Sciences  Control,  Reliability,  Safety  Risk  Statistical  Methods Clasificación: 51 Matemáticas Resumen: Bayesian Reliability presents modern methods and techniques for analyzing reliability data from a Bayesian perspective. The adoption and application of Bayesian methods in virtually all branches of science and engineering have significantly increased over the past few decades. This increase is largely due to advances in simulation-based computational tools for implementing Bayesian methods. The authors extensively use such tools throughout this book, focusing on assessing the reliability of components and systems with particular attention to hierarchical models and models incorporating explanatory variables. Such models include failure time regression models, accelerated testing models, and degradation models. The authors pay special attention to Bayesian goodness-of-fit testing, model validation, reliability test design, and assurance test planning. Throughout the book, the authors use Markov chain Monte Carlo (MCMC) algorithms for implementing Bayesian analyses--algorithms that make the Bayesian approach to reliability computationally feasible and conceptually straightforward. This book is primarily a reference collection of modern Bayesian methods in reliability for use by reliability practitioners. There are more than 70 illustrative examples, most of which utilize real-world data. This book can also be used as a textbook for a course in reliability and contains more than 160 exercises. Noteworthy highlights of the book include Bayesian approaches for the following: Goodness-of-fit and model selection methods Hierarchical models for reliability estimation Fault tree analysis methodology that supports data acquisition at all levels in the tree Bayesian networks in reliability analysis Analysis of failure count and failure time data collected from repairable systems, and the assessment of various related performance criteria Nota de contenido: Reliability Concepts -- Bayesian Inference -- Advanced Bayesian Modeling and Computational Methods -- Component Reliability -- System Reliability -- Repairable System Reliability -- Regression Models in Reliability -- Using Degradation Data to Assess Reliability -- Planning for Reliability Data Collection -- Assurance Testing En línea: http://dx.doi.org/10.1007/978-0-387-77950-8 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34240 Bayesian Reliability [documento electrónico] / Michael S. Hamada ; SpringerLink (Online service) ; Alyson G. Wilson ; C. Shane Reese ; Harry F. Martz . - New York, NY : Springer New York, 2008 . - XVI, 436 p : online resource. - (Springer Series in Statistics, ISSN 0172-7397) . ISBN : 978-0-387-77950-8 Idioma : Inglés (eng) Palabras clave: Mathematics  Probabilities  Statistics  Quality  control  Reliability  Industrial  safety  Probability  Theory  and  Stochastic  Processes  for  Engineering,  Physics,  Computer  Science,  Chemistry  Earth  Sciences  Control,  Reliability,  Safety  Risk  Statistical  Methods Clasificación: 51 Matemáticas Resumen: Bayesian Reliability presents modern methods and techniques for analyzing reliability data from a Bayesian perspective. The adoption and application of Bayesian methods in virtually all branches of science and engineering have significantly increased over the past few decades. This increase is largely due to advances in simulation-based computational tools for implementing Bayesian methods. The authors extensively use such tools throughout this book, focusing on assessing the reliability of components and systems with particular attention to hierarchical models and models incorporating explanatory variables. Such models include failure time regression models, accelerated testing models, and degradation models. The authors pay special attention to Bayesian goodness-of-fit testing, model validation, reliability test design, and assurance test planning. Throughout the book, the authors use Markov chain Monte Carlo (MCMC) algorithms for implementing Bayesian analyses--algorithms that make the Bayesian approach to reliability computationally feasible and conceptually straightforward. This book is primarily a reference collection of modern Bayesian methods in reliability for use by reliability practitioners. There are more than 70 illustrative examples, most of which utilize real-world data. This book can also be used as a textbook for a course in reliability and contains more than 160 exercises. Noteworthy highlights of the book include Bayesian approaches for the following: Goodness-of-fit and model selection methods Hierarchical models for reliability estimation Fault tree analysis methodology that supports data acquisition at all levels in the tree Bayesian networks in reliability analysis Analysis of failure count and failure time data collected from repairable systems, and the assessment of various related performance criteria Nota de contenido: Reliability Concepts -- Bayesian Inference -- Advanced Bayesian Modeling and Computational Methods -- Component Reliability -- System Reliability -- Repairable System Reliability -- Regression Models in Reliability -- Using Degradation Data to Assess Reliability -- Planning for Reliability Data Collection -- Assurance Testing En línea: http://dx.doi.org/10.1007/978-0-387-77950-8 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34240

Ejemplares

Signatura	Medio	Ubicación	Sub-localización	Sección	Estado
ningún ejemplar

Statistical Methods in Counterterrorism / SpringerLink (Online service) ; Alyson G. Wilson ; Wilson, Gregory D ; David H. Olwell (2006)  

Público ISBD Título : Statistical Methods in Counterterrorism : Game Theory, Modeling, Syndromic Surveillance, and Biometric Authentication Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Alyson G. Wilson ; Wilson, Gregory D ; David H. Olwell Editorial: New York, NY : Springer New York Fecha de publicación: 2006 Número de páginas: XII, 292 p. 14 illus Il.: online resource ISBN/ISSN/DL: 978-0-387-35209-1 Idioma : Inglés (eng) Palabras clave: Statistics  Pattern  recognition  Game  theory  Operations  research  Management  science  Economic  Statistical  Theory  and  Methods  Theory,  Economics,  Social  Behav.  Sciences  Theory/Quantitative  Economics/Mathematical  Signal,  Image  Speech  Processing  Recognition  Research,  Science Clasificación: 51 Matemáticas Resumen: All the data was out there to warn us of this impending attack, why didn't we see it?" This was a frequently asked question in the weeks and months after the terrorist attacks on the World Trade Center and the Pentagon on September 11, 2001. In the wake of the attacks, statisticians moved quickly to become part of the national response to the global war on terror. This book is an overview of the emerging research program at the intersection of national security and statistical sciences. A wide range of talented researchers address issues in . Syndromic Surveillance---How do we detect and recognize bioterrorist events? . Modeling and Simulation---How do we better understand and explain complex processes so that decision makers can take the best course of action? . Biometric Authentication---How do we pick the terrorist out of the crowd of faces or better match the passport to the traveler? . Game Theory---How do we understand the rules that terrorists are playing by? This book includes technical treatments of statistical issues that will be of use to quantitative researchers as well as more general examinations of quantitative approaches to counterterrorism that will be accessible to decision makers with stronger policy backgrounds. Dr. Alyson G. Wilson is a statistician and the technical lead for DoD programs in the Statistical Sciences Group at Los Alamos National Laboratory. Dr. Gregory D. Wilson is a rhetorician and ethnographer in the Statistical Sciences Group at Los Alamos National Laboratory. Dr. David H. Olwell is chair of the Department of Systems Engineering at the Naval Postgraduate School in Monterey, California Nota de contenido: Game Theory -- Game Theory in an Age of Terrorism: How Can Statisticians Contribute? -- Combining Game Theory and Risk Analysis in Counterterrorism: A Smallpox Example -- Game-Theoretic and Reliability Methods in Counterterrorism and Security -- Biometric Authentication -- Biometric Authentication -- Towards Statistically Rigorous Biometric Authentication Using Facial Images -- Recognition Problem of Biometrics: Nonparametric Dependence Measures and Aggregated Algorithms -- Syndromic Surveillance -- Data Analysis Research Issues and Emerging Public Health Biosurveillance Directions -- Current and Potential Statistical Methods for Monitoring Multiple Data Streams for Biosurveillance -- Evaluating Statistical Methods for Syndromic Surveillance -- A Spatiotemporal Analysis of Syndromic Data for Biosurveillance -- Modeling -- Modeling and Simulation for Defense and National Security -- Modeling and Parameterization for a Smallpox Simulation Study -- Approaches to Modeling the Concentration Field for Adaptive Sampling of Contaminants during Site Decontamination -- Secure Statistical Analysis of Distributed Databases -- Statistical Evaluation of the Impact of Background Suppression on the Sensitivity of Passive Radiation Detectors En línea: http://dx.doi.org/10.1007/0-387-35209-0 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34816 Statistical Methods in Counterterrorism : Game Theory, Modeling, Syndromic Surveillance, and Biometric Authentication [documento electrónico] / SpringerLink (Online service) ; Alyson G. Wilson ; Wilson, Gregory D ; David H. Olwell . - New York, NY : Springer New York, 2006 . - XII, 292 p. 14 illus : online resource. ISBN : 978-0-387-35209-1 Idioma : Inglés (eng) Palabras clave: Statistics  Pattern  recognition  Game  theory  Operations  research  Management  science  Economic  Statistical  Theory  and  Methods  Theory,  Economics,  Social  Behav.  Sciences  Theory/Quantitative  Economics/Mathematical  Signal,  Image  Speech  Processing  Recognition  Research,  Science Clasificación: 51 Matemáticas Resumen: All the data was out there to warn us of this impending attack, why didn't we see it?" This was a frequently asked question in the weeks and months after the terrorist attacks on the World Trade Center and the Pentagon on September 11, 2001. In the wake of the attacks, statisticians moved quickly to become part of the national response to the global war on terror. This book is an overview of the emerging research program at the intersection of national security and statistical sciences. A wide range of talented researchers address issues in . Syndromic Surveillance---How do we detect and recognize bioterrorist events? . Modeling and Simulation---How do we better understand and explain complex processes so that decision makers can take the best course of action? . Biometric Authentication---How do we pick the terrorist out of the crowd of faces or better match the passport to the traveler? . Game Theory---How do we understand the rules that terrorists are playing by? This book includes technical treatments of statistical issues that will be of use to quantitative researchers as well as more general examinations of quantitative approaches to counterterrorism that will be accessible to decision makers with stronger policy backgrounds. Dr. Alyson G. Wilson is a statistician and the technical lead for DoD programs in the Statistical Sciences Group at Los Alamos National Laboratory. Dr. Gregory D. Wilson is a rhetorician and ethnographer in the Statistical Sciences Group at Los Alamos National Laboratory. Dr. David H. Olwell is chair of the Department of Systems Engineering at the Naval Postgraduate School in Monterey, California Nota de contenido: Game Theory -- Game Theory in an Age of Terrorism: How Can Statisticians Contribute? -- Combining Game Theory and Risk Analysis in Counterterrorism: A Smallpox Example -- Game-Theoretic and Reliability Methods in Counterterrorism and Security -- Biometric Authentication -- Biometric Authentication -- Towards Statistically Rigorous Biometric Authentication Using Facial Images -- Recognition Problem of Biometrics: Nonparametric Dependence Measures and Aggregated Algorithms -- Syndromic Surveillance -- Data Analysis Research Issues and Emerging Public Health Biosurveillance Directions -- Current and Potential Statistical Methods for Monitoring Multiple Data Streams for Biosurveillance -- Evaluating Statistical Methods for Syndromic Surveillance -- A Spatiotemporal Analysis of Syndromic Data for Biosurveillance -- Modeling -- Modeling and Simulation for Defense and National Security -- Modeling and Parameterization for a Smallpox Simulation Study -- Approaches to Modeling the Concentration Field for Adaptive Sampling of Contaminants during Site Decontamination -- Secure Statistical Analysis of Distributed Databases -- Statistical Evaluation of the Impact of Background Suppression on the Sensitivity of Passive Radiation Detectors En línea: http://dx.doi.org/10.1007/0-387-35209-0 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34816

Ejemplares

Signatura	Medio	Ubicación	Sub-localización	Sección	Estado
ningún ejemplar