# distplyr 0.1.2

• 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().

# distplyr 0.1.1

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.

# distplyr 0.1.0

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.