statsmodels.tsa.holtwinters.SimpleExpSmoothing.fit¶
-
SimpleExpSmoothing.
fit
(smoothing_level=None, optimized=True, start_params=None, initial_level=None, use_brute=True)[source]¶ Fit the model
Parameters: smoothing_level : float, optional
The smoothing_level value of the simple exponential smoothing, if the value is set then this value will be used as the value.
optimized : bool, optional
Estimate model parameters by maximizing the log-likelihood
start_params : ndarray, optional
Starting values to used when optimizing the fit. If not provided, starting values are determined using a combination of grid search and reasonable values based on the initial values of the data
initial_level : float, optional
Value to use when initializing the fitted level.
use_brute : bool, optional
Search for good starting values using a brute force (grid) optimizer. If False, a naive set of starting values is used.
Returns: results : HoltWintersResults class
See statsmodels.tsa.holtwinters.HoltWintersResults
Notes
This is a full implementation of the simple exponential smoothing as per [1].
References
- [1] Hyndman, Rob J., and George Athanasopoulos. Forecasting: principles
- and practice. OTexts, 2014.