Changelog
distplyr 0.1.5
 Updates to package infrastructure in the process of migrating to a new GitHub Organization.
distplyr 0.1.3
 Default evaluation methods, and base distributional forms, have been moved to a new package, distionary. distplyr focusses on manipulation verbs only.

Math
method now applies to finite distributions. 
Ops
methods are now available for arithmetic operations (+
,
,*
, and/
) on a single distribution, along with the verbsshift()
,multiply()
,invert()
, andflip()
. 
graft_left()
andgraft_right()
are fully functional, andslice_left()
andslice_right()
are now also available.
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 nowmean()
, etc. For now, the
get_
prefix still holds for distributional representations, likeget_cdf()
.
 For now, the
 Make your own distribution object with
distribution()
instead ofdst()
, and checked withis_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:
 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 withdst()
.
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 momentrelated 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.