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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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Structural tools for seasonal analysis

Data visualization methods have a pivotal role in time series analysis, and in particular with seasonal analysis. As we saw in the preceding examples, the use of data visualization tools allows us to communicate statistical results in an intuitive and insightful way. In the coming sections, we will introduce built-in tools for seasonal analysis with the forecast and TSstudio packages.

Seasonal analysis with the forecast package

The forecast package provides several functions for seasonal analysis based on the ggplot2 package graphics engine (and the base plot function) and it supports the ts objects. The ggseasonplot function creates a seasonal plot of the series by splitting and plotting...

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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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