statsmodels.tsa.holtwinters.SimpleExpSmoothing

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

Simple Exponential Smoothing

Parameters
endogarray-like

Time series

Returns
resultsSimpleExpSmoothing class

See also

ExponentialSmoothing, Holt

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

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.