Exponential Forecasting System

An Exponential Forecasting System is a forecasting system that implements an exponential forecasting algorithm.

• Context:
  • …
• Example(s):
  • Holt-Winters Forecasting System.
• See: ARIMA Algorithm.

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References

2018

• https://stackoverflow.com/a/48684063
  • QUOTE: Forecasts are calculated using weighted averages where the weights decrease exponentially as observations come from further in the past, the smallest weights are associated with the oldest observations:

simple exponential smoothing go back to last N values
y_t = a * y_t + a * (1-a)^1 * y_t-1 + a * (1-a)^2 * y_t-2 + ... + a*(1-a)^n *  y_t-n


def exponential_smoothing(panda_series, alpha_value):
   ouput=sum([alpha_value * (1 - alpha_value) ** i * x for i, x in 
               enumerate(reversed(panda_series))])
   return ouput
panda_series=mydata.y
smoothing_number=exponential_smoothing(panda_series,0.6) # use a=0.6 or 0.5 your choice, which gives less rms error
estimated_values=testdata.copy() # replace testdata with your test dataset
estimated_values['SES'] = smoothing_number
error=sqrt(mean_squared_error(testdata.y, estimated_values.SES))
print(error)

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