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tsfgrnn 1.0.5

• Now, if the lags are automatically chosen, it is not allowed to use only one autoregressive lag with the additive ormultiplicative transformation (it does not make sense)

tsfgrnn 1.0.4

• autoplot.grnnForecast has been modified to comply with CRAN

tsfgrnn 1.0.3

• citation information has been added

tsfgrnn 1.0.2

• References to the paper describing this package have been added in the documentation

tsfgrnn 1.0.1

• The default transformation is now additive instead of multiplicative.

tsfgrnn 1.0.0

• Automatic computation of smoothing parameter can be done with rolling origin or fixed origin (less accurate, but faster).

• Lags can be selected using forward selection or backward elimination (feature selection techniques)

• Time series cannot be scaled

• The model is built using faster Rcpp code

• An optional transformation to the training samples has been added. It improves forecast accuracy for time series with a trend

tsfgrnn 0.2.0

• Uses Rcpp for speeding up computation of forecasts.

tsfgrnn 0.1.0

• This is the first release of this package.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.