esWrapper: Function wrapper for exponential smoothing.
In ammarsahab/smoothCV: Wrappers and parameter optimization for time series smoothing methods
esWrapper R Documentation
Function wrapper for exponential smoothing.
Description
Function wrapper for exponential smoothing.
Usage
esWrapper(trainset, smoothing, nahead = 0)
Arguments
trainset
A set of univariate time series data. Can be a vector (type double) or a data.table.
smoothing
An object of class HoltWinters
nahead
Number of observations to predict.
Value
A list containing smoothed
(training set, moving averages, and predicted training values)
and forc (forecasted values to use against a test set).
Examples
esWrapper(crudenow$close, HoltWinters(crudenow$close, alpha=0.5, beta=0.5, gamma=F), nahead=10)
ammarsahab/smoothCV documentation built on April 18, 2022, 4:39 p.m.
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| esWrapper | R Documentation |
Function wrapper for exponential smoothing.
Description
Function wrapper for exponential smoothing.
Usage
esWrapper(trainset, smoothing, nahead = 0)
Arguments
trainset |
A set of univariate time series data. Can be a vector (type double) or a data.table. |
smoothing |
An object of class |
nahead |
Number of observations to predict. |
Value
A list containing smoothed
(training set, moving averages, and predicted training values)
and forc (forecasted values to use against a test set).
Examples
esWrapper(crudenow$close, HoltWinters(crudenow$close, alpha=0.5, beta=0.5, gamma=F), nahead=10)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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