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Change Point Analysis For Time Series
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Book Synopsis Sequential Analysis by : Alexander Tartakovsky
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
Book Synopsis Bayesian Time Series Models by : David Barber
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.
Book Synopsis Climate Time Series Analysis by : Manfred Mudelsee
Download or read book Climate Time Series Analysis written by Manfred Mudelsee and published by Springer Science & Business Media. This book was released on 2010-08-26 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: Climate is a paradigm of a complex system. Analysing climate data is an exciting challenge, which is increased by non-normal distributional shape, serial dependence, uneven spacing and timescale uncertainties. This book presents bootstrap resampling as a computing-intensive method able to meet the challenge. It shows the bootstrap to perform reliably in the most important statistical estimation techniques: regression, spectral analysis, extreme values and correlation. This book is written for climatologists and applied statisticians. It explains step by step the bootstrap algorithms (including novel adaptions) and methods for confidence interval construction. It tests the accuracy of the algorithms by means of Monte Carlo experiments. It analyses a large array of climate time series, giving a detailed account on the data and the associated climatological questions. This makes the book self-contained for graduate students and researchers.
Book Synopsis Parametric Statistical Change Point Analysis by : Jie Chen
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.
Book Synopsis Limit Theorems in Change-Point Analysis by : Miklós Csörgö
Download or read book Limit Theorems in Change-Point Analysis written by Miklós Csörgö and published by John Wiley & Sons. This book was released on 1997-12-29 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Change-point problems arise in a variety of experimental and mathematical sciences, as well as in engineering and health sciences. This rigorously researched text provides a comprehensive review of recent probabilistic methods for detecting various types of possible changes in the distribution of chronologically ordered observations. Further developing the already well-established theory of weighted approximations and weak convergence, the authors provide a thorough survey of parametric and non-parametric methods, regression and time series models together with sequential methods. All but the most basic models are carefully developed with detailed proofs, and illustrated by using a number of data sets. Contains a thorough survey of: The Likelihood Approach Non-Parametric Methods Linear Models Dependent Observations This book is undoubtedly of interest to all probabilists and statisticians, experimental and health scientists, engineers, and essential for those working on quality control and surveillance problems. Foreword by David Kendall
Book Synopsis Forecasting: principles and practice by : Rob J Hyndman
Download or read book Forecasting: principles and practice written by Rob J Hyndman and published by OTexts. This book was released on 2018-05-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Book Synopsis Change Point Analysis for Time Series by : Lajos Horváth
Download or read book Change Point Analysis for Time Series written by Lajos Horváth and published by Springer Nature. This book was released on with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Density Ratio Estimation in Machine Learning by : Masashi Sugiyama
Download or read book Density Ratio Estimation in Machine Learning written by Masashi Sugiyama and published by Cambridge University Press. This book was released on 2012-02-20 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces theories, methods and applications of density ratio estimation, a newly emerging paradigm in the machine learning community.
Author :Torben Gustav Andersen Publisher :Springer Science & Business Media ISBN 13 :3540712976 Total Pages :1045 pages Book Rating :4.5/5 (47 download)
Book Synopsis Handbook of Financial Time Series by : Torben Gustav Andersen
Download or read book Handbook of Financial Time Series written by Torben Gustav Andersen and published by Springer Science & Business Media. This book was released on 2009-04-21 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.
Book Synopsis Analysis of Time Series Structure by : Nina Golyandina
Download or read book Analysis of Time Series Structure written by Nina Golyandina and published by CRC Press. This book was released on 2001-01-23 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last 15 years, singular spectrum analysis (SSA) has proven very successful. It has already become a standard tool in climatic and meteorological time series analysis and well known in nonlinear physics and signal processing. However, despite the promise it holds for time series applications in other disciplines, SSA is not widely known among statisticians and econometrists, and although the basic SSA algorithm looks simple, understanding what it does and where its pitfalls lay is by no means simple. Analysis of Time Series Structure: SSA and Related Techniques provides a careful, lucid description of its general theory and methodology. Part I introduces the basic concepts, and sets forth the main findings and results, then presents a detailed treatment of the methodology. After introducing the basic SSA algorithm, the authors explore forecasting and apply SSA ideas to change-point detection algorithms. Part II is devoted to the theory of SSA. Here the authors formulate and prove the statements of Part I. They address the singular value decomposition (SVD) of real matrices, time series of finite rank, and SVD of trajectory matrices. Based on the authors' original work and filled with applications illustrated with real data sets, this book offers an outstanding opportunity to obtain a working knowledge of why, when, and how SSA works. It builds a strong foundation for successfully using the technique in applications ranging from mathematics and nonlinear physics to economics, biology, oceanology, social science, engineering, financial econometrics, and market research.
Book Synopsis Change-point Problems by : Edward G. Carlstein
Download or read book Change-point Problems written by Edward G. Carlstein and published by IMS. This book was released on 1994 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Activity Learning by : Diane J. Cook
Download or read book Activity Learning written by Diane J. Cook and published by John Wiley & Sons. This book was released on 2015-02-06 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Defines the notion of an activity model learned from sensor data and presents key algorithms that form the core of the field Activity Learning: Discovering, Recognizing and Predicting Human Behavior from Sensor Data provides an in-depth look at computational approaches to activity learning from sensor data. Each chapter is constructed to provide practical, step-by-step information on how to analyze and process sensor data. The book discusses techniques for activity learning that include the following: Discovering activity patterns that emerge from behavior-based sensor data Recognizing occurrences of predefined or discovered activities in real time Predicting the occurrences of activities The techniques covered can be applied to numerous fields, including security, telecommunications, healthcare, smart grids, and home automation. An online companion site enables readers to experiment with the techniques described in the book, and to adapt or enhance the techniques for their own use. With an emphasis on computational approaches, Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data provides graduate students and researchers with an algorithmic perspective to activity learning.
Book Synopsis Detection of Abrupt Changes by : Michèle Basseville
Download or read book Detection of Abrupt Changes written by Michèle Basseville and published by . This book was released on 1993 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents mathematical tools and techniques for solving change detection problems in wide domains like signal processing, controlled systems and monitoring. The book covers a wide class of stochastic processes, including scalar independent observations and multidimensional dependent ARMA.
Book Synopsis Long Memory in Economics by : Gilles Teyssière
Download or read book Long Memory in Economics written by Gilles Teyssière and published by Springer Science & Business Media. This book was released on 2006-09-22 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Assembles three different strands of long memory analysis: statistical literature on the properties of, and tests for, LRD processes; mathematical literature on the stochastic processes involved; and models from economic theory providing plausible micro foundations for the occurrence of long memory in economics.
Book Synopsis Statistical Methods and Modeling of Seismogenesis by : Nikolaos Limnios
Download or read book Statistical Methods and Modeling of Seismogenesis written by Nikolaos Limnios and published by John Wiley & Sons. This book was released on 2021-04-27 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: The study of earthquakes is a multidisciplinary field, an amalgam of geodynamics, mathematics, engineering and more. The overriding commonality between them all is the presence of natural randomness. Stochastic studies (probability, stochastic processes and statistics) can be of different types, for example, the black box approach (one state), the white box approach (multi-state), the simulation of different aspects, and so on. This book has the advantage of bringing together a group of international authors, known for their earthquake-specific approaches, to cover a wide array of these myriad aspects. A variety of topics are presented, including statistical nonparametric and parametric methods, a multi-state system approach, earthquake simulators, post-seismic activity models, time series Markov models with regression, scaling properties and multifractal approaches, selfcorrecting models, the linked stress release model, Markovian arrival models, Poisson-based detection techniques, change point detection techniques on seismicity models, and, finally, semi-Markov models for earthquake forecasting.
Book Synopsis Analyzing Neural Time Series Data by : Mike X Cohen
Download or read book Analyzing Neural Time Series Data written by Mike X Cohen and published by MIT Press. This book was released on 2014-01-17 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to the conceptual, mathematical, and implementational aspects of analyzing electrical brain signals, including data from MEG, EEG, and LFP recordings. This book offers a comprehensive guide to the theory and practice of analyzing electrical brain signals. It explains the conceptual, mathematical, and implementational (via Matlab programming) aspects of time-, time-frequency- and synchronization-based analyses of magnetoencephalography (MEG), electroencephalography (EEG), and local field potential (LFP) recordings from humans and nonhuman animals. It is the only book on the topic that covers both the theoretical background and the implementation in language that can be understood by readers without extensive formal training in mathematics, including cognitive scientists, neuroscientists, and psychologists. Readers who go through the book chapter by chapter and implement the examples in Matlab will develop an understanding of why and how analyses are performed, how to interpret results, what the methodological issues are, and how to perform single-subject-level and group-level analyses. Researchers who are familiar with using automated programs to perform advanced analyses will learn what happens when they click the “analyze now” button. The book provides sample data and downloadable Matlab code. Each of the 38 chapters covers one analysis topic, and these topics progress from simple to advanced. Most chapters conclude with exercises that further develop the material covered in the chapter. Many of the methods presented (including convolution, the Fourier transform, and Euler's formula) are fundamental and form the groundwork for other advanced data analysis methods. Readers who master the methods in the book will be well prepared to learn other approaches.
Download or read book R Cookbook written by Paul Teetor and published by "O'Reilly Media, Inc.". This book was released on 2011-03-03 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: With more than 200 practical recipes, this book helps you perform data analysis with R quickly and efficiently. The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and output, general statistics, graphics, and linear regression. Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an experienced data programmer, it will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process. Create vectors, handle variables, and perform other basic functions Input and output data Tackle data structures such as matrices, lists, factors, and data frames Work with probability, probability distributions, and random variables Calculate statistics and confidence intervals, and perform statistical tests Create a variety of graphic displays Build statistical models with linear regressions and analysis of variance (ANOVA) Explore advanced statistical techniques, such as finding clusters in your data "Wonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language—one practical example at a time."—Jeffrey Ryan, software consultant and R package author
