The LOGSHASH is introduced as a distribution in the 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 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 at https://github.com/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.