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Hands-On Time Series Analysis with R

You're reading from   Hands-On Time Series Analysis with R Perform time series analysis and forecasting using R

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781788629157
Length 448 pages
Edition 1st Edition
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Author (1):
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Rami Krispin Rami Krispin
Author Profile Icon Rami Krispin
Rami Krispin
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Table of Contents (14) Chapters Close

Preface 1. Introduction to Time Series Analysis and R 2. Working with Date and Time Objects FREE CHAPTER 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

Manipulating the zoo and xts objects

One of the main advantages of the zoo class and, in particular, the xts class (with respect to the ts object), is their friendly and simple structure. This allows us to preprocess and manipulate these types of objects in a seamless manner. Both the zoo and the xts packages provide a variety of utility functions for working with these types of objects. In this section, we will introduce some of the main functions for manipulating the zoo and xts objects.

Merging time series objects

In some instances, you may want to join or merge different series into a single object. Both the zoo and xts packages provide functions for merging a time series object (including merging mixed classes, such as...

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