class statsmodels.tsa.holtwinters.HoltWintersResults(model, params, **kwds) [source]
Holt Winter’s Exponential Smoothing Results
| Parameters: |
|
|---|
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.
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