NEWS
utsf 1.3.3 (2026-04-22)
- The param parameter in the regression function provided by the user is
changed to a ... parameter.
- Extreme gradient boosting is supported using the xgboost package.
utsf 1.3.2 (2026-04-14)
- The model tree is now built with the parameter committees set to 5
- The param parameter used to set arguments to the regression models in the
create_model function is no longer needed, you can set the arguments directly.
utsf 1.3.1 (2025-10-23)
- The pre-processing for dealing with trending series is now specified in a
simpler way.
- The vignette has been improved.
- The way in which tuning parameters are specified to user's models has changed.
utsf 1.3.0 (2025-07-08)
- 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 (2025-05-19)
- 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 (2024-12-10)
- 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 (2024-10-14)