statsmodels.tsa.holtwinters.SimpleExpSmoothing

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

Simple Exponential Smoothing wrapper(…)

Parameters: endog (array-like) – Time series
Returns: results
Return type: SimpleExpSmoothing class

Notes

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

See also

Exponential, Holt

References

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

Methods

fit([smoothing_level, optimized]) fit Simple Exponential Smoothing wrapper(…)
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
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.

Attributes

endog_names Names of endogenous variables
exog_names

© 2009–2012 Statsmodels Developers
© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.
http://www.statsmodels.org/stable/generated/statsmodels.tsa.holtwinters.SimpleExpSmoothing.html