statsmodels.tsa.holtwinters.SimpleExpSmoothing

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

Simple Exponential Smoothing

Parameters:

endog : array-like

Time series
Returns:

results : SimpleExpSmoothing class

See also

ExponentialSmoothing, Holt

Notes

This is a full implementation of the simple exponential smoothing as per [R35]. SimpleExpSmoothing is a restricted version of ExponentialSmoothing.

References

[R35](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
initial_values() Compute initial values used in the exponential smoothing recursions
initialize() 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.