class statsmodels.tsa.holtwinters.SimpleExpSmoothing(endog) [source]
Simple Exponential Smoothing wrapper(…)
| Parameters: | endog (array-like) – Time series |
|---|---|
| Returns: | results |
| Return type: | SimpleExpSmoothing class |
This is a full implementation of the simple exponential smoothing as per [1].
See also
Exponential, Holt
[1] Hyndman, Rob J., and George Athanasopoulos. Forecasting: principles and practice. OTexts, 2014.
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. |
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