Lecture 16 – A few examples of using ARIMA#

Contents of this lecture

  • Basic concept of time series analysis example

  • Data pre-processing, visualization and analysis (trend, periodic, seasonal, error analysis)

  • Stationary and nonstationary time series

  • Missing data in the time series

  • ACF, PACF and their usage for ARIMA(p, d, q)

  • Qualify and quantity the predictability of time series

  • Improve forecast by using other series (Granger causality test)

  • ARIMA and its application examples

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Please download the lecture through the following link Lecture 16 – A few examples of using ARIMA