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Data Science 101: Forecasting Time Series Using R

An integral tool found in data science is Time Series Forecasting. Here is a useful instructional video on the subject from one of the authors of a free eBook available on OTexts – “Forecasting: Principles and Practice.” The presentation “Forecasting Time Series Using R” is made by Professor of Statistics Rob J Hyndman. You can download the slides and R scripts HERE.

Hyndman looks at the various facilities for time series forecasting available in R, concentrating on the forecast package. This package implements several automatic methods for forecasting time series including forecasts from ARIMA models, ARFIMA models and exponential smoothing models. He also looks more generally at how to go about forecasting non-seasonal data, seasonal data, seasonal data with high frequency, and seasonal data with multiple frequencies. Examples will be taken from his own consulting experience. He also gives an overview of what’s possible and available and where it is useful, rather than give the mathematical details of any specific time series methods.

 

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