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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

Concepts

Author (1):

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

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Correlation between two variables

One of the main goals of correlation analysis is to identify and quantify the relationship between two variables. This relationship could vary from having a full dependency or linear relationship between the two, to complete independence. One of the most popular methods for measuring the level of correlation between two variables is the Pearson correlation coefficient. Although this method is not necessarily the most appropriate one for time series data, it is a simple and intuitive representative of the statistical logic beyond most of the methods for measuring correlation. This method, also known as the population correlation coefficient, is a ratio between the covariance of two variables and the multiplication of their standard deviation:

The values of the correlation coefficient segment the level of correlation into three main groups:

Positively...

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Authors (1)

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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