The LOGSHASH is introduced as a distribution with
range (0, Inf). It could be fitted before but it had to be generated by
the function gen.Family,
i.e. gen.Family("SHASH", "log").
The LOGSHASHo is also introduced as a distribution
in the range (0, Inf) but at the moment remains hidden.
count_1_23 e.t.c. were checked.The dPO, pPO and qPO are
updated so the length of y is equal to the length of
mu
the functions test_continuous_gamlss_dist() and
test_discrete_gamlss_dist() are added to the package for
checking distributions but the functions not have help files.
BCT the BCPE and the BCCG
have new d, p and q
functions
the q functions for all distributions are updated so
the limits are defined properly for example for the BEINF we have;
– q[abs(p-0)<1e-15] <- 0
– q[abs(p-1)<1e-15] <- Inf
– q[p < 0] <- NaN
– q[p > 1] <- NaN.
gamlss-dev organization: https://github.com/gamlss-dev/gamlss/.The package is now hosted on GitHub
(mstasinopoulos/GAMLSS-Distibutions).
Add an S3 class GAMLSS and corresponding methods
encompassing all distributions from the gamlss.dist package
using the workflow from the distributions3
package (contributed by Achim
Zeileis). The idea is that from fitted gamlss model
objects predicted probability distributions can be obtained for which
moments (mean, variance, etc.), probabilities, quantiles, etc. can be
obtained with corresponding generic functions. See useR! 2022
presentation by Zeileis, Lang, and Hayes for an overview of the
distributions3 package.