statsmodels/statsmodels — pull request #1287 by ccsv (2014-01-04 09:46:51+00:00)
Title: Made Exponential Smoothing for Statsmodel handles Single, double, triple (Needs Checking and improvements) 

Started Exponential Model off of code from dfrusdn and heavily modified. Handles 15 different models. The code is also fully documented. It looked like this was in demand so I tried out my coding skills.

This handles ALL of the following models:
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

The code is accurate just that the initial values are off so they have to be adjusted. All the equations match what is given by Exponential smoothing: The state of the Art II page 8.

I do not know what methods are used to backcast the function so I left two Nans in the beginning to align the data. There is also a todo list.

I am not a programmer and I just did python for about 3 months so I need a code check. I think this should be in a class but I have not dealt with them enough to know what I am doing.