- If you have the tibble package installed, distplyr will now output tibbles wherever data frames were previously output.
get_ prefix has been removed from distributional quantities.
get_mean() is now
- For now, the
get_ prefix still holds for distributional representations, like
- Make your own distribution object with
distribution() instead of
dst(), and checked with
This patch both fixes some problems in the previous release, as well as offering a step towards a bigger expansion.
- Some change in the functional representations:
- Changed random number generation from
randfn, a functional representation, to the
probfn representation to be more specific:
- Added the
enframe suite of functions.
- Implement the beginnings of being able to specify your own distribution, with the
set_ suite of functions, after making an empty distribution with
Additionally, there’s some internal rearrangement, where the
get functions call the
eval functions, not vice versa.
The first version of
distplyr is now available! Its functionality is rather limited at the moment, but is still useful, especially for its capability to handle a discrete component of a distribution. Here are the main features:
- Base distributions include step distributions, Gaussian, Uniform, and generalized Pareto.
- Operations include grafting (right) and mixing
- Distribution properties included are moment-related quantities, and extreme value index.
- Distribution representations are mostly comprehensive, perhaps only missing mean excess function and moment generating function.
Take a look at the “Vision” vignette to get a sense of where this package is headed.