This cycle adds support objects: a distribution now says where it
places its probability, and the routines computing from it — quantiles
and moments — use that to handle atoms exactly rather than
approximately. Code that uses the built-in dst_*()
distributions is unaffected. Most of the breaking changes are in
distribution(), so they reach only distributions built by
hand; the exception is length() and is.na(),
which now answer about the distribution itself.
distribution() now requires a .support,
saying where the distribution places probability. See
?distribution, and the “The Support of a Distribution”
vignette for why it is asked for.
.vtype is defunct, and errors with a message
pointing at .support. The variable type is derived from the
support.
range and vtype are derived from the
support rather than stated, and distribution() refuses them
as entries. Both remain properties, reachable through
eval_property() like any other.
length(), is.na() and
as.list() answer about the distribution rather than about
the list of properties it is built from: length() gives 1,
not 11, and is.na() gives a single logical,
TRUE for the Null distribution. The properties are
unchanged; see ?length.dst.
New support objects say where a distribution places probability,
tracking its atoms explicitly: discrete(),
continuous(), and
mixed(discrete =, continuous =). Retrieve one with
support(), its two parts with atoms() and
regions(), and test one with
is_support().
empty_support(), with
is_empty_support(). No distribution has an empty support,
but operations on supports need something to return.
Supports can now be manipulated, not only built:
support_union(), support_restrict() and
support_transform(), with support_shift(),
support_scale() and support_reciprocal() for
the common maps; support_add_atoms() and
support_drop_atoms(); and support_contains()
and support_has_atom(). There is deliberately no
intersection.
All built-in dst_*() families carry a support, so
their atoms are known explicitly — dst_pois() reports the
atoms 0, 1, 2, ....
Re-exported the discretes constructors used to
describe atomic supports, so they work without attaching that package:
natural0(), natural1(),
integers(), arithmetic() and
as_discretes().
Moments (mean(), variance(),
stdev(), skewness(), kurtosis())
are computed numerically for discrete and mixed distributions, not only
continuous ones: a sum over the atoms plus integration over the regions.
Infinite atomic supports are walked outward, and a moment that never
settles returns NaN.
Quantiles derived through the property network are considerably
faster, solving every requested probability in one vectorised bisection
rather than a separate search for each. A probability landing inside an
atom’s jump returns that atom exactly, and the 0- and 1-quantiles come
from the support, so an unbounded distribution gives -Inf
and Inf. Discrete and mixed distributions raised an error
on this path before.
dst_pearson3(), and the underlying
ppearson3(), dpearson3(),
qpearson3() and rpearson3(), accept a negative
shape: the Pearson Type III reflected about
location, giving the negatively-skewed, upper-bounded
form.
dst_lp3() supports negative skew on the log scale.
Zero skew is treated as a log-normal distribution.
Replaced usage of the deprecated ellipsis package
with rlang for checking expected use of ellipsis (thanks to
@olivroy, PR
#44).
dst_lp3() now prints the created distribution object
upon creation, matching the behaviour of other dst_*()
functions.