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Hands-On Time Series Analysis with R

You're reading from  Hands-On Time Series Analysis with R

Product type Book
Published in May 2019
Publisher Packt
ISBN-13 9781788629157
Pages 448 pages
Edition 1st Edition
Languages
Author (1):
Rami Krispin Rami Krispin
Profile icon Rami Krispin
Toc

Table of Contents (14) Chapters close

Preface 1. Introduction to Time Series Analysis and R 2. Working with Date and Time Objects 3. The Time Series Object 4. Working with zoo and xts Objects 5. Decomposition of Time Series Data 6. Seasonality Analysis 7. Correlation Analysis 8. Forecasting Strategies 9. Forecasting with Linear Regression 10. Forecasting with Exponential Smoothing Models 11. Forecasting with ARIMA Models 12. Forecasting with Machine Learning Models 13. Other Books You May Enjoy

Data manipulation of ts objects

The data preprocessing does not complete once the series is transformed into a ts object because, in many cases, you may be required to apply some additional transformation or preprocessing steps. This includes steps such as extracting or subsetting a specific element of the series or aggregating the series to a different frequency (for example, from monthly to quarterly). A typical example of such a step is splitting the series into training and testing partitions when training a forecasting model. Due to the unique structure of the ts object, in most cases, the common extraction methods for data.frame do not apply to ts objects. In this section, we will introduce methods and designated functions for data manipulation of ts objects by using the window, aggregate, and other functions.

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