Applied Time Series Analysis with R

Time series analysis is a method for analyzing data that changes over time. Examples include stock prices, the cost of money, and the jobless rate. Applied Time Series Analysis with R, Second Edition, is a book that teaches students how to use and understand the tools of applied time series analysis. It includes examples from a variety of fields, develops theory, and provides an R-based software package to help students solve real-world problems. The book is organized for graduate students in statistics and the natural and social sciences and includes over 150 exercises and extensive support for instructors.

Format: Paperback / softback
Length: 636 pages
Publication date: 30 June 2021
Publisher: Taylor & Francis Ltd

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.

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).

Weight: 924g
Dimension: 156 x 232 x 41 (mm)
ISBN-13: 9781032097220
Edition number: 2 New edition