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Hands-On Time Series Analysis with R

You're reading from  Hands-On Time Series Analysis with R

Product type Book
Published in May 2019
Publisher Packt
ISBN-13 9781788629157
Pages 448 pages
Edition 1st Edition
Languages
Author (1):
Rami Krispin Rami Krispin
Profile icon Rami Krispin

Table of Contents (14) Chapters

Preface 1. Introduction to Time Series Analysis and R 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

Visualizing ts and mts objects

One of the first things that you probably want to do once you create or convert your data to a ts or mts format is to visualize it. This step is a quick sanity check to make sure that your data looks like you expect it would and to identify outliers, seasonality, and other patterns within your data. There are two approaches for visualizing a time series object:

  • Direct: This approach uses a visualization function to plot the object without any data transformation or conversion to another class. There are few packages that provide direct tools for visualizing time series objects. In this chapter, we will focus on three packages:
    • stats: In addition to the ts objects, this provides the plot.ts function for visualizing time series objects. This function is an extension of the plot function, which is an R built-in visualization function.
    • dygraphs: This...
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