Название: Applied Time Series Analysis with R, Second Edition Автор: Wayne A. Woodward, Henry L. Gray
Издательство: CRC Press
ISBN: 1498734227
Год: 2016
Страниц: 634
Язык: английский
Формат: epub
Размер: 14.4 MB
Virtually any random process developing chronologically can be viewed as a time series. In economics closing prices of stocks, the cost of money, the jobless rate, and retail sales are just a few examples of many. Developed from course notes and extensively classroom-tested, Applied Time Series Analysis with R, Second Edition includes examples across a variety of fields, develops theory, and provides an R-based software package to aid in addressing time series problems in a broad spectrum of fields. The material is organized in an optimal format for graduate students in statistics as well as in the natural and social sciences to learn to use and understand the tools of applied time series analysis.
Suggestions concerning the first edition were as follows: (1) to base the computing on R and (2) to include more real data examples. To address item (1) we have created an R package, tswge, which is available in CRAN to accompany this book. Extensive discussion of the use of tswge functions is given within the chapters and in appendices following each chapter. The tswge package currently has about 40 functions and that number may continue to grow. We have added guidance concerning R usage throughout the entire book. Of special note is the fact that R support is now provided for Chapters 10 through 13. In the first edition, the accompanying software package GW-WINKS contained only limited computational support related to these chapters.
Features:
Gives readers the ability to actually solve significant real-world problems
Addresses many types of nonstationary time series and cutting-edge methodologies
Promotes understanding of the data and associated models rather than viewing it as the output of a "black box"
Provides the R package tswge available on CRAN which contains functions and over 100 real and simulated data sets to accompany the book. Extensive help regarding the use of tswge functions is provided in appendices and on an associated website.
Over 150 exercises and extensive support for instructors
The second edition includes additional real-data examples, uses R-based code that helps students easily analyze data, generate realizations from models, and explore the associated characteristics. It also adds discussion of new advances in the analysis of long memory data and data with time-varying frequencies (TVF).
Скачать Applied Time Series Analysis with R, Second Edition