Información del autor
Autor Wu, Yanhong |
Documentos disponibles escritos por este autor (2)
Refinar búsqueda
Título : Inference for Change Point and Post Change Means After a CUSUM Test Tipo de documento: documento electrónico Autores: Wu, Yanhong ; SpringerLink (Online service) Editorial: New York, NY : Springer New York Fecha de publicación: 2005 Colección: Lecture Notes in Statistics, ISSN 0930-0325 num. 180 Número de páginas: XIII, 158 p Il.: online resource ISBN/ISSN/DL: 978-0-387-26269-7 Idioma : Inglés (eng) Palabras clave: Mathematics Probabilities Statistics Quality control Reliability Industrial safety Econometrics Probability Theory and Stochastic Processes Statistical Methods for Engineering, Physics, Computer Science, Chemistry Earth Sciences Control, Reliability, Safety Risk Business/Economics/Mathematical Finance/Insurance Clasificación: 51 Matemáticas Resumen: This monograph is the first to systematically study the bias of estimators and construction of corrected confidence intervals for change-point and post-change parameters after a change is detected by using a CUSUM procedure. Researchers in change-point problems and sequential analysis, time series and dynamic systems, and statistical quality control will find that the methods and techniques are mostly new and can be extended to more general dynamic models where the structural and distributional parameters are monitored. Practitioners, who are interested in applications to quality control, dynamic systems, financial markets, clinical trials and other areas, will benefit from case studies based on data sets from river flow, accident interval, stock prices, and global warming. Readers with an elementary probability and statistics background and some knowledge of CUSUM procedures will be able to understand most results as the material is relatively self-contained. The exponential family distribution is used as the basic model that includes changes in mean, variance, and hazard rate as special cases. There are fundamental differences between the sequential sampling plan and fixed sample size. Although the results are given under the CUSUM procedure, the methods and techniques discussed provide new approaches to deal with inference problems after sequential change-point detection, and they also contribute to the theoretical aspects of sequential analysis. Many results are of independent interests and can be used to study random walk related stochastic models. Yanhong Wu is a visiting lecturer in statistics at the University of the Pacific. Previously, he was a visiting associate professor at the University of Michigan and an assistant professor at the University of Alberta. He has published more than forty research papers on the topics of change-point problem, quality control, mixture models, risk theory, and reliability mathematics. He was the receiver of Pierre-Robillard Award from the Canadian Statistical Society. Nota de contenido: CUSUM Procedure -- Change-Point Estimation -- Confidence Interval for Change-Point -- Inference for Post-Change Mean -- Estimation After False Signal -- Inference with Change in Variance -- Sequential Classification and Segmentation -- An Adaptive CUSUM Procedure -- Dependent Observation Case -- Other Methods and Remarks En línea: http://dx.doi.org/10.1007/b100107 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=35096 Inference for Change Point and Post Change Means After a CUSUM Test [documento electrónico] / Wu, Yanhong ; SpringerLink (Online service) . - New York, NY : Springer New York, 2005 . - XIII, 158 p : online resource. - (Lecture Notes in Statistics, ISSN 0930-0325; 180) .
ISBN : 978-0-387-26269-7
Idioma : Inglés (eng)
Palabras clave: Mathematics Probabilities Statistics Quality control Reliability Industrial safety Econometrics Probability Theory and Stochastic Processes Statistical Methods for Engineering, Physics, Computer Science, Chemistry Earth Sciences Control, Reliability, Safety Risk Business/Economics/Mathematical Finance/Insurance Clasificación: 51 Matemáticas Resumen: This monograph is the first to systematically study the bias of estimators and construction of corrected confidence intervals for change-point and post-change parameters after a change is detected by using a CUSUM procedure. Researchers in change-point problems and sequential analysis, time series and dynamic systems, and statistical quality control will find that the methods and techniques are mostly new and can be extended to more general dynamic models where the structural and distributional parameters are monitored. Practitioners, who are interested in applications to quality control, dynamic systems, financial markets, clinical trials and other areas, will benefit from case studies based on data sets from river flow, accident interval, stock prices, and global warming. Readers with an elementary probability and statistics background and some knowledge of CUSUM procedures will be able to understand most results as the material is relatively self-contained. The exponential family distribution is used as the basic model that includes changes in mean, variance, and hazard rate as special cases. There are fundamental differences between the sequential sampling plan and fixed sample size. Although the results are given under the CUSUM procedure, the methods and techniques discussed provide new approaches to deal with inference problems after sequential change-point detection, and they also contribute to the theoretical aspects of sequential analysis. Many results are of independent interests and can be used to study random walk related stochastic models. Yanhong Wu is a visiting lecturer in statistics at the University of the Pacific. Previously, he was a visiting associate professor at the University of Michigan and an assistant professor at the University of Alberta. He has published more than forty research papers on the topics of change-point problem, quality control, mixture models, risk theory, and reliability mathematics. He was the receiver of Pierre-Robillard Award from the Canadian Statistical Society. Nota de contenido: CUSUM Procedure -- Change-Point Estimation -- Confidence Interval for Change-Point -- Inference for Post-Change Mean -- Estimation After False Signal -- Inference with Change in Variance -- Sequential Classification and Segmentation -- An Adaptive CUSUM Procedure -- Dependent Observation Case -- Other Methods and Remarks En línea: http://dx.doi.org/10.1007/b100107 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=35096 Ejemplares
Signatura Medio Ubicación Sub-localización Sección Estado ningún ejemplar
Título : Probability and Statistical Models : Foundations for Problems in Reliability and Financial Mathematics Tipo de documento: documento electrónico Autores: Arjun K. Gupta ; SpringerLink (Online service) ; Zeng, Wei-Bin ; Wu, Yanhong Editorial: Boston, MA : Birkhäuser Boston Fecha de publicación: 2010 Otro editor: Imprint: Birkhäuser Número de páginas: XII, 267 p Il.: online resource ISBN/ISSN/DL: 978-0-8176-4987-6 Idioma : Inglés (eng) Palabras clave: Mathematics Economics, Mathematical models Probabilities Statistics Applied mathematics Engineering Probability Theory and Stochastic Processes for Business/Economics/Mathematical Finance/Insurance Appl.Mathematics/Computational Methods of Modeling Industrial Engineering, Physics, Computer Science, Chemistry Earth Sciences Quantitative Finance Clasificación: 51 Matemáticas Resumen: With an emphasis on models and techniques, this textbook introduces many of the fundamental concepts of stochastic modeling that are now a vital component of almost every scientific investigation. These models form the basis of well-known parametric lifetime distributions such as exponential, Weibull, and gamma distributions, as well as change-point and mixture models. The authors also consider more general notions of non-parametric lifetime distribution classes. In particular, emphasis is placed on laying the foundation for solving problems in reliability, insurance, finance, and credit risk. Exercises and solutions to selected problems accompany each chapter in order to allow students to explore these foundations. The key subjects covered include: * Exponential distributions and the Poisson process * Parametric lifetime distributions * Non-parametric lifetime distribution classes * Multivariate exponential extensions * Association and dependence * Renewal theory * Problems in reliability, insurance, finance, and credit risk This work differs from traditional probability textbooks in a number of ways. Since no measure theory knowledge is necessary to understand the material and coverage of the central limit theorem and normal theory related topics has been omitted, the work may be used as a single-semester senior undergraduate or first-year graduate textbook as well as in a second course on probability modeling. Many of the chapters that examine central topics in applied probability can be read independently, allowing both instructors and readers extra flexibility in their use of the book. Probability and Statistical Models is for a wide audience including advanced undergraduate and beginning-level graduate students, researchers, and practitioners in mathematics, statistics, engineering, and economics Nota de contenido: Preliminaries -- Exponential Distribution -- Poisson Process -- Parametric Families of Lifetime Distributions -- Lifetime Distribution Classes -- Multivariate Lifetime Distributions -- Association and Dependence -- Renewal Theory -- Risk Theory -- Asset Pricing Theory -- Credit Risk Modeling En línea: http://dx.doi.org/10.1007/978-0-8176-4987-6 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33565 Probability and Statistical Models : Foundations for Problems in Reliability and Financial Mathematics [documento electrónico] / Arjun K. Gupta ; SpringerLink (Online service) ; Zeng, Wei-Bin ; Wu, Yanhong . - Boston, MA : Birkhäuser Boston : Imprint: Birkhäuser, 2010 . - XII, 267 p : online resource.
ISBN : 978-0-8176-4987-6
Idioma : Inglés (eng)
Palabras clave: Mathematics Economics, Mathematical models Probabilities Statistics Applied mathematics Engineering Probability Theory and Stochastic Processes for Business/Economics/Mathematical Finance/Insurance Appl.Mathematics/Computational Methods of Modeling Industrial Engineering, Physics, Computer Science, Chemistry Earth Sciences Quantitative Finance Clasificación: 51 Matemáticas Resumen: With an emphasis on models and techniques, this textbook introduces many of the fundamental concepts of stochastic modeling that are now a vital component of almost every scientific investigation. These models form the basis of well-known parametric lifetime distributions such as exponential, Weibull, and gamma distributions, as well as change-point and mixture models. The authors also consider more general notions of non-parametric lifetime distribution classes. In particular, emphasis is placed on laying the foundation for solving problems in reliability, insurance, finance, and credit risk. Exercises and solutions to selected problems accompany each chapter in order to allow students to explore these foundations. The key subjects covered include: * Exponential distributions and the Poisson process * Parametric lifetime distributions * Non-parametric lifetime distribution classes * Multivariate exponential extensions * Association and dependence * Renewal theory * Problems in reliability, insurance, finance, and credit risk This work differs from traditional probability textbooks in a number of ways. Since no measure theory knowledge is necessary to understand the material and coverage of the central limit theorem and normal theory related topics has been omitted, the work may be used as a single-semester senior undergraduate or first-year graduate textbook as well as in a second course on probability modeling. Many of the chapters that examine central topics in applied probability can be read independently, allowing both instructors and readers extra flexibility in their use of the book. Probability and Statistical Models is for a wide audience including advanced undergraduate and beginning-level graduate students, researchers, and practitioners in mathematics, statistics, engineering, and economics Nota de contenido: Preliminaries -- Exponential Distribution -- Poisson Process -- Parametric Families of Lifetime Distributions -- Lifetime Distribution Classes -- Multivariate Lifetime Distributions -- Association and Dependence -- Renewal Theory -- Risk Theory -- Asset Pricing Theory -- Credit Risk Modeling En línea: http://dx.doi.org/10.1007/978-0-8176-4987-6 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33565 Ejemplares
Signatura Medio Ubicación Sub-localización Sección Estado ningún ejemplar
