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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 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

Summary

This chapter provided an overview of time series analysis with R. We started with the basic definition of time series data and the analysis process, which we will use throughout this book. In addition, we discussed the uses of R for time series analysis. This included the packages and the datasets we will use in this book. Last but not least, we provided a brief introduction to the R programming languages so that we could align them with the R prerequisites of this book.

In the next chapter, we will focus on the date and time object, one of the core elements of the time series object.

You have been reading a chapter from
Hands-On Time Series Analysis with R
Published in: May 2019
Publisher: Packt
ISBN-13: 9781788629157
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