Create a model object as an interim step to a theta method forecast.
A numeric vector or time series.
This fits an exponential smoothing state space model with
model = 'ANN' to
having first performed classic multiplicative seasonal adjustment. A drift value is also calculated
lsfit(0:(length(y) - 1), y)$coef / 2. In combination with
forecast.thetam(), this provides
identical results to
forecast::thetaf(...). The purpose of splitting it into a 'model' and
'forecast' functions is to make the approach consistent with other modelling / forecasting approaches
An object of class
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