# statsmodels.tsa.holtwinters.SimpleExpSmoothing¶

class statsmodels.tsa.holtwinters.SimpleExpSmoothing(endog)[source]

Simple Exponential Smoothing

Parameters
endogarray-like

Time series

Returns
resultsSimpleExpSmoothing class

Notes

This is a full implementation of the simple exponential smoothing as per [1]. SimpleExpSmoothing is a restricted version of ExponentialSmoothing.

References

1(1,2)

Hyndman, Rob J., and George Athanasopoulos. Forecasting: principles and practice. OTexts, 2014.

Attributes
endog_names

Names of endogenous variables

exog_names

Methods

 fit([smoothing_level, optimized, …]) Fit the model from_formula(formula, data[, subset, drop_cols]) Create a Model from a formula and dataframe. hessian(params) The Hessian matrix of the model information(params) Fisher information matrix of model Compute initial values used in the exponential smoothing recursions Initialize (possibly re-initialize) a Model instance. loglike(params) Log-likelihood of model. predict(params[, start, end]) Returns in-sample and out-of-sample prediction. score(params) Score vector of model.