function LR_test is modified to allow 'gamlss2' objects.
the functions GAIC() and Rsq() are now generic function
the functions Rsq() and GAIC() have become generic function so they can
be used in conjunction with the package gamlss2
the functions GAIC.scaled() and GAIC.table() have been renamed as
GAIC_scaled() and GAIC_table(), respectively, so the name do not class with the
generic function GAIC().
Tim Cole's suggestion in predictAll() is added. This is to deal
with the problem when mu is fixed.
Tim Cole's suggestion in summary()is added. This to fix the
problem when y~0, (that is, when there are no df's), to be
incorporated in the summary.gamlss().
predict() do not print the message "new prediction"
stepGAIC() produce less lines in the output
The package is now hosted on GitHub at https://github.com/gamlss-dev/gamlss/.
Add a new prodist() method for extracting fitted (in-sample) or
predicted (out-of-sample) probability distributions from gamlss
models (contributed by Achim Zeileis).
This enables the workflow from the
distributions3
package for all distributions provided by gamlss.dist. The idea is
that the distributions3 objects encapsulate all information needed
to obtain moments (mean, variance, etc.), probabilities, quantiles,
etc. with a unified interface. See the useR! 2022
presentation by Zeileis,
Lang, and Hayes for an overview.