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Identify time-series forecasting algorithm

I'm trying to build an algorithm in C# based on these videos (CLICK!) My question is not related to the coding part of these tasks.

I'm trying to gain a deeper understanding of this algorithm since it is perfect for my assignment. However, the YouTuber doesn't identify it by name.I'd like to know any information that you can give me -- name, resources, etc.

Edit: It's Time-series decomposition model. Specifically, classical multiplicative decomposition.

Steps:

  1. Calculate a moving average equal to the length of the season to identify the trend cycle.
  2. Center the moving average if the seasonal length is an even number.
  3. Calculate the actual as a proportion of the centered moving average to obtain the seasonal index for each period.
  4. Adjust the total of the seasonal indexes to equal the number of periods.
  5. Deseasonalized the time series by dividing it by the seasonal index.
  6. Estimated the trend-cyclical regression using deseasonalized data.
  7. Multiply the fitted trend values by their appropriate seasonal factors to compute the fitted values
  8. Calculate the errors and measure the accuracy of the fit using known actual series.
  9. If cyclical factors are important, calculate cyclical indexes.
  10. Check for outliers, adjust the actual series and repeat steps from 1 to 9 if necessary
Solution

  • It is a well known, well documented, identifiable algorithm.

    One of the comments to the video says "What you did is Moving Average, can you please show us how to do Auto Regressive (AR) and Auto Regressive Moving Average (ARMA) if it is possible in Excel?"

    You can learn about MA, AR, and AR(I)MA from this book - https://otexts.com/fpp2/