distributions3 0.2.0

Vectorized univariate distribution objects by Moritz Lang and Achim Zeileis (#71 and #82). This allows representation of fitted probability distributions from regression models. New helper functions are provided to help setting up such distribution objects in a unified way. In particular, apply_dpqr() helps to apply the standard d/p/q/r functions available in base R and many packages. The accompanying manual page provides some worked examples and further guidance.
New vignette (by Achim Zeileis) on using distributions3 to go from basic probability theory to probabilistic regression models. Illustrated with Poisson GLMs for the number of goals per team in the 2018 FIFA World Cup explained by the teams’ ability differences. (#74)
New generic function prodist() to extract fitted (in-sample) or predicted (out-of-sample) probability distributions from model objects like lm, glm, or arima. (#83)
Extended support for count data distributions (by Achim Zeileis): Alternative parameterization for negative binomial distribution (commonly used in regression models), zero-inflated Poisson, and zero-hurdle Poisson. (#80 and #81)

distributions3 0.1.2

Added a plotting generic for univariate distributions (@paulnorthrop, PR #56)
Added support for the Generalised Extreme Value (GEV), Frechet, Gumbel, reversed Weibull and Generalised Pareto (GP) distributions (@paulnorthrop, PR #52)
Added support for the Erlang distribution (@ellessenne, PR #54)
Various minor bug fixes