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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

Product type Paperback

Published in May 2019

Publisher Packt

ISBN-13 9781788629157

Length 448 pages

Edition 1st Edition

Languages

R

Tools

Plotly

Concepts

Data Analysis

Author (1):

Rami Krispin

View More author details

Table of Contents (14) Chapters

Preface

1. Introduction to Time Series Analysis and R FREE CHAPTER

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

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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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Authors (1)

Rami Krispin

Rami Krispin

Rami Krispin is a data scientist at a major Silicon Valley company, where he focuses on time series analysis and forecasting. In his free time, he also develops open source tools and is the author of several R packages, including the TSstudio package for time series analysis and forecasting applications. Rami holds an MA in Applied Economics and an MS in actuarial mathematics from the University of MichiganAnn Arbor.

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