The Analysis of Time Series: An Introduction with R, 7th Edition

The Analysis of Time Series: An Introduction with R, 7th Edition 电子书 第1张The Analysis of Time Series: An Introduction with R, 7th Edition
The Analysis of Time Series: An Introduction with R, 7th Edition
By 作者: Chris Chatfield
Series: Chapman & Hall/CRC Texts in Statistical Science
pages 页数: 414 pages
Publisher Finelybook 出版社: Routledge; 7 edition (May 9, 2019)
Language 语言: English
ISBN-10 书号:1498795633
ISBN-13 书号:9781498795630
The Book Description robot was collected from Amazon and arranged by Finelybook
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.


Contents


Preface to the Seventh Edition
Abbreviations and Notation
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
References
Index

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