mantar 0.2.0
- The argument
k, which controlled the penalty term in
information-criterion calculations, has been removed for security
reasons. Instead, the penalty type is now specified via the argument
ic_type (see the corresponding help pages).
New defaults
- Changed the default handling of the
ridge penalty in
the multiple-imputation pmm workflow when looking for
donors through regressions (mice). Instead of forcing
ridge = 0, the function now uses the default value defined
by mice, ensuring consistent and method-appropriate
regularization.
New features
- Added function
reg_network() for network estimation
using regularization, supporting both convex and non-convex penalties as
well as multiple options for computing the likelihood in the information
criterion when missing values are present.
- Added function
ordered_suggest(), a heuristic procedure
for identifying variables that may be treated as ordered categorical
based on their distribution and available information.
- Added dummy data sets
mantar_dummy_full_cat and
mantar_dummy_mis_cat, containing only ordered categorical
variables (with and without missing values).
- Added dummy data sets
mantar_dummy_full_mix and
mantar_dummy_mis_mix, containing mixtures of ordered
categorical and continuous variables (with and without missing
values).
Improvements
- Added support for treating variables as ordered categorical in the
estimation of correlations.
- Renamed dummy data sets to
mantar_dummy_full_cont and
mantar_dummy_mis_cont to better reflect that they contain
only continuous variables.
- Improved documentation for several functions and updated the README
to reflect new functionality.
mantar 0.1.0