Solved – Exponential smoothing models backcasting and determining initial values python

exponential-smoothingpythonstarting valuestime series

I have made python code for exponential smoothing (ES) that takes in about 15 different cases including:

  • Simple Exponential Smoothing (SES)
  • Simple Seasonal models (both multiplicative and additive)
  • Brown's Linear Exponential Smoothing
  • Holt's Double Exponential Smoothing
  • Exponential trend method
  • Damped-Trend Linear Exponential Smoothing
  • Multiplicative damped trend (Taylor, 2003)
  • Holt-Winters Exponential Smoothing: multiplicative trend, additive trend, multiplicative season, additive season, and damped models for all four variations

14 of these cases can be found in page 8 of Exponential smoothing: The state of the art Part II.

What values are commonly used for the initial values for the different ES models? What methods are used to determine points at time 0 and 1? (I am using Nan (not a number) to substitute in the code right now).

Best Answer

Some common choices for initial values are given at the bottom of https://www.otexts.org/fpp/7/6.

However, it is much better to optimize the initial values along with the smoothing parameters.

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