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statsmodels.tsa.holtwinters.HoltWintersResults

class statsmodels.tsa.holtwinters.HoltWintersResults(model, params, **kwds) [source]

Holt Winter’s Exponential Smoothing Results

Parameters:
  • model (ExponentialSmoothing instance) – The fitted model instance
  • params (dictionary) – All the parameters for the Exponential Smoothing model.
specification

dictionary – Dictionary including all attributes from the VARMAX model instance.

params

dictionary – All the parameters for the Exponential Smoothing model.

fittedfcast

array – An array of both the fitted values and forecast values.

fittedvalues

array – An array of the fitted values. Fitted by the Exponential Smoothing model.

fcast

array – An array of the forecast values forecast by the Exponential Smoothing model.

sse

float – The sum of squared errors

level

array – An array of the levels values that make up the fitted values.

slope

array – An array of the slope values that make up the fitted values.

season

array – An array of the seaonal values that make up the fitted values.

aic

float – The Akaike information criterion.

bic

float – The Bayesian information criterion.

aicc

float – AIC with a correction for finite sample sizes.

resid

array – An array of the residuals of the fittedvalues and actual values.

k

int – the k parameter used to remove the bias in AIC, BIC etc.

Methods

forecast([steps]) Out-of-sample forecasts
initialize(model, params, **kwd)
predict([start, end]) In-sample prediction and out-of-sample forecasting
summary()

© 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.HoltWintersResults.html