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.
utsf 1.2.0
- 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.
utsf 1.1.0
- Improvements in estimation of forecast accuracy with rolling origin
evaluation.
- The way in which pre-processings are specified has changed.
- Method plot.utsf is implemented.
- Linear models (stats::lm) are supported.
utsf 1.0.0