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Hands-On Time Series Analysis with R
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Table of Contents

Table of Contents

  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

About the Author

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 Michigan-Ann Arbor.

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