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The Analysis of Time Series: An Introduction with R by Chris Chatfield: New
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Specificaties
- Objectstaat
- Book Title
- The Analysis of Time Series: An Introduction with R
- Publication Date
- 2019-05-08
- Edition Number
- 7
- ISBN
- 9781138066137
- Subject Area
- Mathematics
- Publication Name
- Analysis of Time Series : an Introduction with R
- Publisher
- CRC Press LLC
- Item Length
- 9.2 in
- Subject
- Probability & Statistics / General, Probability & Statistics / Time Series
- Publication Year
- 2019
- Series
- Chapman and Hall/Crc Texts in Statistical Science Ser.
- Type
- Textbook
- Format
- Hardcover
- Language
- English
- Item Weight
- 25.7 Oz
- Item Width
- 6.1 in
- Number of Pages
- 398 Pages
Over dit product
Product Identifiers
Publisher
CRC Press LLC
ISBN-10
1138066133
ISBN-13
9781138066137
eBay Product ID (ePID)
25038746589
Product Key Features
Number of Pages
398 Pages
Language
English
Publication Name
Analysis of Time Series : an Introduction with R
Publication Year
2019
Subject
Probability & Statistics / General, Probability & Statistics / Time Series
Type
Textbook
Subject Area
Mathematics
Series
Chapman and Hall/Crc Texts in Statistical Science Ser.
Format
Hardcover
Dimensions
Item Weight
25.7 Oz
Item Length
9.2 in
Item Width
6.1 in
Additional Product Features
Edition Number
7
Intended Audience
College Audience
LCCN
2019-006743
Reviews
"Chris Chatfield has already written some popular books in statistics. Haipeng Xing is also a renowned researcher in statistics with more than 8000 citation. Efforts have been made by both authors to publish reliable data and information relating to different applications... The best part of the book is that some exercises are explained explicitly with sufficient hints. The authors also review several books on time series by other researchers from 1971 to 2010...Overall, this book is a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis in a wide range of topics. The book is intended for masters and undergraduate students in mathematics, probability, economics, statistics, astrophysics, biomedical engineering, and neuroscience. However, students who are early in a relevant PhD programme should also read this book to gain fundamental background knowledge." - Chitaranjan Mahapatra, ISCB News, July 2020 "One would never fail to notice the accessibility and the patience with which the authors introduce each of the topics in this classical textbook. The new edition successfully continues the style of the past editions, to be the one of the most accessible textbook on time series analysis. It introduces the topics with intuitions, followed with the most necessary technical details. I am particularly pleased that the R-code and data sets accompanying all the graphical analysis throughout the book, appear right where the definitions are introduced, satisfying the immediate curiosity of the readers. Together with the homework, they provide a nice platform to engage in description, explanation, prediction and control using time series data. Many data sets are updated or newly incorporated, relative to the previous version. A must-read for anyone interested in an introduction to time series." - Feng Yao, West Virginia University
TitleLeading
The
Illustrated
Yes
Table Of Content
1. Introduction 2. Basic Descriptive Techniques 3. Some Linear Time Series Models 4. Fitting Time Series Models in the Time Domain 5. Forecasting 6. Stationary Processes in the Frequency Domain 7. Spectral Analysis 8. Bivariate Processes 9. Linear Systems 10. State-Space Models and the Kalman Filter 11. Non-Linear Models 12. Volatility Models 13. Multivariate Time Series Modelling 14. Some More Advanced Topics Appendix A Fourier, Laplace, and z-Transforms. Appendix B Dirac Delta Function. Appendix C Covariance and Correlation. Answers to Exercises.
Synopsis
This new edition of this classic title, now in its seventh edition, presents a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis., This new edition of this classic title, now in its seventh edition, presents a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis. The book covers a wide range of topics, including ARIMA models, forecasting methods, spectral analysis, linear systems, state-space models, the Kalman filters, nonlinear models, volatility models, and multivariate models., A new chapter on univariate volatility models A revised chapter on linear time series models A new section on multivariate volatility models A new section on regime switching models Many new worked examples, with R code integrated into the text, This new edition of this classic title, now in its seventh edition, presents a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis. The book covers a wide range of topics, including ARIMA models, forecasting methods, spectral analysis, linear systems, state-space models, the Kalman filters, nonlinear models, volatility models, and multivariate models. It also presents many examples and implementations of time series models and methods to reflect advances in the field. Highlights of the seventh edition: A new chapter on univariate volatility models A revised chapter on linear time series models A new section on multivariate volatility models A new section on regime switching models Many new worked examples, with R code integrated into the text The book can be used as a textbook for an undergraduate or a graduate level time series course in statistics. The book does not assume many prerequisites in probability and statistics, so it is also intended for students and data analysts in engineering, economics, and finance.
LC Classification Number
QA280.C4 2019
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