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Author : Heng Yang
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (961 download)
Download or read book Stochastic Processes And Their Applications To Change Point Detection Problems written by Heng Yang and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : David Barber
Publisher : Cambridge University Press
ISBN 13 : 0521196760
Total Pages : 432 pages
Book Rating : 4.5/5 (211 download)
Download or read book Bayesian Time Series Models written by David Barber and published by Cambridge University Press. This book was released on 2011-08-11 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first unified treatment of time series modelling techniques spanning machine learning, statistics, engineering and computer science.
Author : E. Brodsky
Publisher : Springer Science & Business Media
ISBN 13 : 9401581630
Total Pages : 221 pages
Book Rating : 4.4/5 (15 download)
Download or read book Nonparametric Methods in Change Point Problems written by E. Brodsky and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: The explosive development of information science and technology puts in new problems involving statistical data analysis. These problems result from higher re quirements concerning the reliability of statistical decisions, the accuracy of math ematical models and the quality of control in complex systems. A new aspect of statistical analysis has emerged, closely connected with one of the basic questions of cynergetics: how to "compress" large volumes of experimental data in order to extract the most valuable information from data observed. De tection of large "homogeneous" segments of data enables one to identify "hidden" regularities in an object's behavior, to create mathematical models for each seg ment of homogeneity, to choose an appropriate control, etc. Statistical methods dealing with the detection of changes in the characteristics of random processes can be of great use in all these problems. These methods have accompanied the rapid growth in data beginning from the middle of our century. According to a tradition of more than thirty years, we call this sphere of statistical analysis the "theory of change-point detection. " During the last fifteen years, we have witnessed many exciting developments in the theory of change-point detection. New promising directions of research have emerged, and traditional trends have flourished anew. Despite this, most of the results are widely scattered in the literature and few monographs exist. A real need has arisen for up-to-date books which present an account of important current research trends, one of which is the theory of non parametric change--point detection.
Author : Ansgar Steland
Publisher : Springer Nature
ISBN 13 : 3030286657
Total Pages : 450 pages
Book Rating : 4.0/5 (32 download)
Download or read book Stochastic Models, Statistics and Their Applications written by Ansgar Steland and published by Springer Nature. This book was released on 2019-10-15 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents selected and peer-reviewed contributions from the 14th Workshop on Stochastic Models, Statistics and Their Applications, held in Dresden, Germany, on March 6-8, 2019. Addressing the needs of theoretical and applied researchers alike, the contributions provide an overview of the latest advances and trends in the areas of mathematical statistics and applied probability, and their applications to high-dimensional statistics, econometrics and time series analysis, statistics for stochastic processes, statistical machine learning, big data and data science, random matrix theory, quality control, change-point analysis and detection, finance, copulas, survival analysis and reliability, sequential experiments, empirical processes, and microsimulations. As the book demonstrates, stochastic models and related statistical procedures and algorithms are essential to more comprehensively understanding and solving present-day problems arising in e.g. the natural sciences, machine learning, data science, engineering, image analysis, genetics, econometrics and finance.
Author : Boris Brodsky
Publisher : CRC Press
ISBN 13 : 1498755976
Total Pages : 366 pages
Book Rating : 4.4/5 (987 download)
Download or read book Change-Point Analysis in Nonstationary Stochastic Models written by Boris Brodsky and published by CRC Press. This book was released on 2016-12-12 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the development of methods for detection and estimation of changes in complex systems. These systems are generally described by nonstationary stochastic models, which comprise both static and dynamic regimes, linear and nonlinear dynamics, and constant and time-variant structures of such systems. It covers both retrospective and sequential problems, particularly theoretical methods of optimal detection. Such methods are constructed and their characteristics are analyzed both theoretically and experimentally. Suitable for researchers working in change-point analysis and stochastic modelling, the book includes theoretical details combined with computer simulations and practical applications. Its rigorous approach will be appreciated by those looking to delve into the details of the methods, as well as those looking to apply them.
Author : Boris Brodsky
Publisher : CRC Press
ISBN 13 : 1315350955
Total Pages : 286 pages
Book Rating : 4.3/5 (153 download)
Download or read book Change-Point Analysis in Nonstationary Stochastic Models written by Boris Brodsky and published by CRC Press. This book was released on 2016-12-12 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the development of methods for detection and estimation of changes in complex systems. These systems are generally described by nonstationary stochastic models, which comprise both static and dynamic regimes, linear and nonlinear dynamics, and constant and time-variant structures of such systems. It covers both retrospective and sequential problems, particularly theoretical methods of optimal detection. Such methods are constructed and their characteristics are analyzed both theoretically and experimentally. Suitable for researchers working in change-point analysis and stochastic modelling, the book includes theoretical details combined with computer simulations and practical applications. Its rigorous approach will be appreciated by those looking to delve into the details of the methods, as well as those looking to apply them.
Author : Jie Chen
Publisher : Springer Science & Business Media
ISBN 13 : 1475731310
Total Pages : 190 pages
Book Rating : 4.4/5 (757 download)
Download or read book Parametric Statistical Change Point Analysis written by Jie Chen and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently there has been a keen interest in the statistical analysis of change point detec tion and estimation. Mainly, it is because change point problems can be encountered in many disciplines such as economics, finance, medicine, psychology, geology, litera ture, etc. , and even in our daily lives. From the statistical point of view, a change point is a place or time point such that the observations follow one distribution up to that point and follow another distribution after that point. Multiple change points problem can also be defined similarly. So the change point(s) problem is two fold: one is to de cide if there is any change (often viewed as a hypothesis testing problem), another is to locate the change point when there is a change present (often viewed as an estimation problem). The earliest change point study can be traced back to the 1950s. During the fol lowing period of some forty years, numerous articles have been published in various journals and proceedings. Many of them cover the topic of single change point in the means of a sequence of independently normally distributed random variables. Another popularly covered topic is a change point in regression models such as linear regres sion and autoregression. The methods used are mainly likelihood ratio, nonparametric, and Bayesian. Few authors also considered the change point problem in other model settings such as the gamma and exponential.
Author : Jun Geng
Publisher :
ISBN 13 :
Total Pages : 282 pages
Book Rating : 4.:/5 (916 download)
Download or read book Quickest Change-Point Detection with Sampling Right Constraints written by Jun Geng and published by . This book was released on 2015 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: The quickest change-point detection problems with sampling right constraints are considered. Specially, an observer sequentially takes observations from a random sequence, whose distribution will change at an unknown time. Based on the observation sequence, the observer wants to identify the change-point as quickly as possible. Unlike the classic quickest detection problem in which the observer can take an observation at each time slot, we impose a causal sampling right constraint to the observer. In particular, sampling rights are consumed when the observer takes an observation and are replenished randomly by a stochastic process. The observer cannot take observations if there is no sampling right left. The causal sampling right constraint is motivated by several practical applications. For example, in the application of sensor network for monitoring the abrupt change of its ambient environment, the sensor can only take observations if it has energy left in its battery. With this additional constraint, we design and analyze the optimal detection and sampling right allocation strategies to minimize the detection delay under various problem setups. As one of our main contributions, a greedy sampling right allocation strategy, by which the observer spends sampling rights in taking observations as long as there are sampling rights left, is proposed. This strategy possesses a low complexity structure, and leads to simple but (asymptotically) optimal detection algorithms for the problems under consideration. Specially, our main results include: 1) Non-Bayesian quickest change-point detection: we consider non-Bayesian quickest detection problem with stochastic sampling right constraint. Two criteria, namely the algorithm level average run length (ARL) and the system level ARL, are proposed to control the false alarm rate. We show that the greedy sampling right allocation strategy combined with the cumulative sum (CUSUM) algorithm is optimal for Lorden's setup with the algorithm level ARL constraint and is asymptotically optimal for both Lorden's and Pollak's setups with the system level ARL constraint. 2) Bayesian quickest change-point detection: both limited sampling right constraint and stochastic sampling right constraint are considered in the Bayesian quickest detection problem. The limited sampling right constraint can be viewed as a special case of the stochastic sampling right constraint with a zero sampling right replenishing rate. The optimal solutions are derived for both sampling right constraints. However, the structure of the optimal solutions are rather complex. For the problem with the limited sampling right constraint, we provide asymptotic upper and lower bounds for the detection delay. For the problem with the stochastic sampling right constraint, we show that the greedy sampling right allocation strategy combined with Shiryaev's detection rule is asymptotically optimal. 3) Quickest change-point detection with unknown post-change parameters: we extend previous results to the quickest detection problem with unknown post- change parameters. Both non-Bayesian and Bayesian setups with stochastic sampling right constraints are considered. For the non-Bayesian problem, we show that the greedy sampling right allocation strategy combined with the M-CUSUM algorithm is asymptotically optimal. For the Bayesian setups, we show that the greedy sampling right allocation strategy combined with the proposed M-Shiryaev algorithm is asymptotically optimal.
Author : Ansgar Steland
Publisher : Springer
ISBN 13 : 3319138812
Total Pages : 479 pages
Book Rating : 4.3/5 (191 download)
Download or read book Stochastic Models, Statistics and Their Applications written by Ansgar Steland and published by Springer. This book was released on 2015-02-04 with total page 479 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents the latest advances and trends in stochastic models and related statistical procedures. Selected peer-reviewed contributions focus on statistical inference, quality control, change-point analysis and detection, empirical processes, time series analysis, survival analysis and reliability, statistics for stochastic processes, big data in technology and the sciences, statistical genetics, experiment design, and stochastic models in engineering. Stochastic models and related statistical procedures play an important part in furthering our understanding of the challenging problems currently arising in areas of application such as the natural sciences, information technology, engineering, image analysis, genetics, energy and finance, to name but a few. This collection arises from the 12th Workshop on Stochastic Models, Statistics and Their Applications, Wroclaw, Poland.
Author : Petar Todorovic
Publisher : Springer Science & Business Media
ISBN 13 : 1461397421
Total Pages : 302 pages
Book Rating : 4.4/5 (613 download)
Download or read book An Introduction to Stochastic Processes and Their Applications written by Petar Todorovic and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text on stochastic processes and their applications is based on a set of lectures given during the past several years at the University of California, Santa Barbara (UCSB). It is an introductory graduate course designed for classroom purposes. Its objective is to provide graduate students of statistics with an overview of some basic methods and techniques in the theory of stochastic processes. The only prerequisites are some rudiments of measure and integration theory and an intermediate course in probability theory. There are more than 50 examples and applications and 243 problems and complements which appear at the end of each chapter. The book consists of 10 chapters. Basic concepts and definitions are pro vided in Chapter 1. This chapter also contains a number of motivating ex amples and applications illustrating the practical use of the concepts. The last five sections are devoted to topics such as separability, continuity, and measurability of random processes, which are discussed in some detail. The concept of a simple point process on R+ is introduced in Chapter 2. Using the coupling inequality and Le Cam's lemma, it is shown that if its counting function is stochastically continuous and has independent increments, the point process is Poisson. When the counting function is Markovian, the sequence of arrival times is also a Markov process. Some related topics such as independent thinning and marked point processes are also discussed. In the final section, an application of these results to flood modeling is presented.
Author :
Publisher :
ISBN 13 : 9783030286668
Total Pages : 449 pages
Book Rating : 4.2/5 (866 download)
Download or read book Stochastic Models, Statistics and Their Applications written by and published by . This book was released on 2019 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents selected and peer-reviewed contributions from the 14th Workshop on Stochastic Models, Statistics and Their Applications, held in Dresden, Germany, on March 6-8, 2019. Addressing the needs of theoretical and applied researchers alike, the contributions provide an overview of the latest advances and trends in the areas of mathematical statistics and applied probability, and their applications to high-dimensional statistics, econometrics and time series analysis, statistics for stochastic processes, statistical machine learning, big data and data science, random matrix theory, quality control, change-point analysis and detection, finance, copulas, survival analysis and reliability, sequential experiments, empirical processes, and microsimulations. As the book demonstrates, stochastic models and related statistical procedures and algorithms are essential to more comprehensively understanding and solving present-day problems arising in e.g. the natural sciences, machine learning, data science, engineering, image analysis, genetics, econometrics and finance.
Author : Nitish V. Thakor
Publisher : Springer Nature
ISBN 13 : 9811655405
Total Pages : 3686 pages
Book Rating : 4.8/5 (116 download)
Download or read book Handbook of Neuroengineering written by Nitish V. Thakor and published by Springer Nature. This book was released on 2023-02-02 with total page 3686 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Handbook serves as an authoritative reference book in the field of Neuroengineering. Neuroengineering is a very exciting field that is rapidly getting established as core subject matter for research and education. The Neuroengineering field has also produced an impressive array of industry products and clinical applications. It also serves as a reference book for graduate students, research scholars and teachers. Selected sections or a compendium of chapters may be used as “reference book” for a one or two semester graduate course in Biomedical Engineering. Some academicians will construct a “textbook” out of selected sections or chapters. The Handbook is also meant as a state-of-the-art volume for researchers. Due to its comprehensive coverage, researchers in one field covered by a certain section of the Handbook would find other sections valuable sources of cross-reference for information and fertilization of interdisciplinary ideas. Industry researchers as well as clinicians using neurotechnologies will find the Handbook a single source for foundation and state-of-the-art applications in the field of Neuroengineering. Regulatory agencies, entrepreneurs, investors and legal experts can use the Handbook as a reference for their professional work as well.
Author : Kenneth D. Lawrence
Publisher : IAP
ISBN 13 : 1623960576
Total Pages : 254 pages
Book Rating : 4.6/5 (239 download)
Download or read book Contemporary Perspectives in Data Mining, Volume 1 written by Kenneth D. Lawrence and published by IAP. This book was released on 2013-04-01 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner. Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted form this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups. Data mining applications are seen in finance (banking, brokerage, insurance), marketing (customer relationships, retailing, logistics, travel), as well as in manufacturing, health care, fraud detection, home-land security, and law enforcement.
Author : Alexander Tartakovsky
Publisher : CRC Press
ISBN 13 : 1439838216
Total Pages : 600 pages
Book Rating : 4.4/5 (398 download)
Download or read book Sequential Analysis written by Alexander Tartakovsky and published by CRC Press. This book was released on 2014-08-27 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sequential Analysis: Hypothesis Testing and Changepoint Detection systematically develops the theory of sequential hypothesis testing and quickest changepoint detection. It also describes important applications in which theoretical results can be used efficiently. The book reviews recent accomplishments in hypothesis testing and changepoint detecti
Author : M. Csörgö
Publisher : American Mathematical Soc.
ISBN 13 : 0821835610
Total Pages : 546 pages
Book Rating : 4.8/5 (218 download)
Download or read book Asymptotic Methods in Stochastics written by M. Csörgö and published by American Mathematical Soc.. This book was released on 2004 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: Honoring over forty years of Miklos Csorgo's work in probability and statistics, this title shows the state of the research. This book covers such topics as: path properties of stochastic processes, weak convergence of random size sums, almost sure stability of weighted maxima, and procedures for detecting changes in statistical models.
Author : Barbara Szyszkowicz
Publisher :
ISBN 13 :
Total Pages : 498 pages
Book Rating : 4.:/5 (29 download)
Download or read book Weak Convergence of Stochastic Processes in Weighted Metrics and Their Applications to Contiguous Changepoint Analysis written by Barbara Szyszkowicz and published by . This book was released on 1992 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Rudolf Dutter
Publisher : Physica
ISBN 13 : 364252463X
Total Pages : 539 pages
Book Rating : 4.6/5 (425 download)
Download or read book Compstat written by Rudolf Dutter and published by Physica. This book was released on 2013-12-20 with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book assembles papers which were presented at the biennial sympo sium in Computational Statistics held und er the a!uspices of the International Association for Statistical Computing (IASC), a section of ISI, the Interna tional Statistical Institute. This symposium named COMPSTAT '94 was organized by the Statistical Institutes of the University of Vienna and the University of Technology of Vienna, Austria. The series of COMPSTAT Symposia started 1974 in Vienna. Mean while they took place every other year in Berlin (Germany, 1976), Leiden (The Netherlands, 1978), Edinburgh (Great Britain, 1980), Toulouse (France, 1982), Prague (Czechoslovakia, 1984), Rom (Italy, 1986), Copenhagen (Den mark, 1988), Dubrovnik (Yugoslavia, 1990) and Neuchätel (Switzerland, 1992). This year we are celebrating the 20th anniversary in Vienna, Austria. It has obviously been observed a movement from "traditional" computa tional statistics with emphasis on methods which produce results quickly and reliably, to computationally intensive methods like resampling procedures, Bayesian methods, dynamic graphics, to very recent areas like neural net works, accentuation on spatial statistics, huge data sets, analysis strategies, etc. For the organization of the symposium, new guidelines worked out by the IASC in written form were in effect this time. The goal was to refresh somehow the spirit of the start of COMPSTAT '74, keep the tradition of the series and ensure a certain continuity in the sequence of biannual meetings.
