utsf 1.3.0

The lags argument in the function for building the model (now create_model) now can be an unordered integer vector.
The lags argument in the function for building the model (now create_model) now must be an integer vector.
match.arg() is used so the options are visible to the user in the help.
A main change is that the functionality of the forecast function, that did a lot of things, is now distributed in several functions: create_model() (build the model), forecast() (do the forecasts), efa() for assessing forecast accuracy and tune_grid() for parameter tuning.
Prediction intervals are optionally computed.

utsf 1.2.1

The default value of parameter transform_features in trend function is again TRUE.

The estimated forecast accuracy per horizon is also computed.
Now it is possible to use only 1 lag with additive or multiplicative transformation, if the features are not transformed.
Now it is possible to transform only the target (and not the features) with the multiplicative transformation.
An error is produced if a too large autorregresive lag is used.
An error is produced in method KNN when k is greater than the size of the training set.
A warning is produced when the time series is too short to estimate forecast accuracy.