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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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Technical requirement

The following packages will be used in this chapter:

forecast: Version 8.5 and above
TSstudio: Version 0.1.4 and above
plotly: Version 4.8 and above
dplyr: Version 0.8.1 and above
lubridate: Version 1.7.4 and above
stats: Version 3.6.0 and above
datasets: Version 3.6.0 and above
base: Version 3.6.0 and above

You can access the codes for this chapter from the following link:

https://github.com/PacktPublishing/Hands-On-Time-Series-Analysis-with-R/tree/master/Chapter11

The rest of the chapter is locked

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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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