- If you have the tibble package installed, distplyr will now output tibbles wherever data frames were previously output.

##
Breaking changes

- The
`get_`

prefix has been removed from distributional quantities. `get_mean()`

is now `mean()`

, etc.
- For now, the
`get_`

prefix still holds for distributional representations, like `get_cdf()`

.

- Make your own distribution object with
`distribution()`

instead of `dst()`

, and checked with `is_distribution()`

.

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 `realise()`

and `realize()`

functions.
- Changed
`probfn`

representation to be more specific: `pmf`

or `density`

- 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 `dst()`

.

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.