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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

Lag plots

A lag plot is a simplistic and non-statistical approach for analyzing the relationship between a series and its lags. As the name indicates, this method is based on data visualization tools, with the use of two-dimensional scatter plots for visualizing the series (typically on the y-axis) against the k lag of the series. Hence, each pair of points represents a combination of the series observations and their corresponding lagged values. As more points on the lag plot are closer to the 45 degree line, the higher the correlation will be between the series and the corresponding lag. The TSstudio package provides a customized function, ts_lags, for creating multiple lag plots. Let's use the function to plot the USgas series against its lags:

ts_lags(USgas) 

We will get the following plot:

Looking at the lag plots of the USgas series, you can see that, moving along...

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