Change Point Analysis For Time Series

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Bayesian Time Series Models

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Author : David Barber
language : en
Publisher: Cambridge University Press
Release Date : 2011-08-11

Bayesian Time Series Models written by David Barber and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-08-11 with Computers categories.

The first unified treatment of time series modelling techniques spanning machine learning, statistics, engineering and computer science.

Parametric Statistical Change Point Analysis

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Author : Jie Chen
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-11

Parametric Statistical Change Point Analysis written by Jie Chen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-11 with Mathematics categories.

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.

Change Point Analysis

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Author : Baisuo Jin
language : en
Publisher: CRC Press
Release Date : 2025-08-29

Change Point Analysis written by Baisuo Jin and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-29 with Mathematics categories.

Change point analysis is a crucial statistical technique for detecting structural breaks within datasets, applicable in diverse fields such as finance and weather forecasting. The authors of this book aim to consolidate recent advancements and broaden the scope beyond traditional time series applications to include biostatistics, longitudinal data analysis, high-dimensional data, and network analysis. The book introduces foundational concepts with practical data examples from literature, alongside discussions of related machine learning topics. Subsequent chapters focus on mathematical tools for single- and multiple-change point detection along with statistical inference issues, which provide rigorous proofs to enhance understanding but assume readers have foundational knowledge in graduate-level probability and statistics. The book also expands the discussion into threshold regression frameworks linked to subgroup identification in modern statistical learning and apply change point analysis to functional data and dynamic networks—areas not comprehensively covered elsewhere. Key Features: Comprehensive Coverage of Diverse Applications: This book expands the scope of change point analysis to include biostatistics, longitudinal data, high-dimensional data, and network analysis. This broad applicability makes it a valuable resource for researchers and students across various disciplines Integration of Theory and Practice: The book balances rigorous mathematical theory with practical applications by providing extensive computational examples using R. Each chapter features real-world data illustrations and discussions of relevant machine learning topics, ensuring that readers can see the relevance of theoretical concepts in applied settings Accessibility for Students: The content is designed with graduate-level students in mind, providing clear explanations and structured guidance through complex mathematical tools. Rigorous proofs are included to facilitate understanding without overwhelming readers with overly advanced theories early on The book incorporates computational results using R, showcasing various packages tailored for specific methods or problem domains while providing references for further exploration. By offering a selection of widely adopted methodologies relevant in scientific research as well as business contexts, this text aims to equip junior researchers with essential tools needed for their work in change point analysis.

Handbook Of Financial Time Series

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Author : Torben Gustav Andersen
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-04-21

Handbook Of Financial Time Series written by Torben Gustav Andersen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-21 with Business & Economics categories.

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.

Density Ratio Estimation In Machine Learning

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Author : Masashi Sugiyama
language : en
Publisher: Cambridge University Press
Release Date : 2012-02-20

Density Ratio Estimation In Machine Learning written by Masashi Sugiyama and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-20 with Computers categories.

This book introduces theories, methods and applications of density ratio estimation, a newly emerging paradigm in the machine learning community.

Forecasting Principles And Practice

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Author : Rob J Hyndman
language : en
Publisher: OTexts
Release Date : 2018-05-08

Forecasting Principles And Practice written by Rob J Hyndman and has been published by OTexts this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-08 with Business & Economics categories.

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.

Activity Learning

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Author : Diane J. Cook
language : en
Publisher: John Wiley & Sons
Release Date : 2015-02-06

Activity Learning written by Diane J. Cook and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-06 with Technology & Engineering categories.

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.

Detection Of Abrupt Changes

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Author : Michèle Basseville
language : en
Publisher:
Release Date : 1993

Detection Of Abrupt Changes written by Michèle Basseville and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Mathematics categories.

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.

Elements Of Multivariate Time Series Analysis

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Author : Gregory C. Reinsel
language : en
Publisher: Springer Science & Business Media
Release Date : 2003-10-31

Elements Of Multivariate Time Series Analysis written by Gregory C. Reinsel and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-10-31 with Mathematics categories.

Now available in paperback, this book introduces basic concepts and methods useful in the analysis and modeling of multivariate time series data. It concentrates on the time-domain analysis of multivariate time series, and assumes univariate time series analysis, while covering basic topics such as stationary processes and their covariance matrix structure, vector AR, MA, and ARMA models, forecasting, least squares and maximum likelihood estimation for ARMA models, associated likelihood ratio testing procedures.

Change Point Analysis In Nonstationary Stochastic Models

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Author : Boris Brodsky
language : en
Publisher: CRC Press
Release Date : 2016-12-12

Change Point Analysis In Nonstationary Stochastic Models written by Boris Brodsky and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-12 with Mathematics categories.

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.