# distr-package

##### distr -- object orientated implementation of distributions

`Distribution`

is introduced with slots for a
parameter and ---most important--- for the four constitutive methods `r`

,
`d`

, `p`

, and `q`

for simulation respectively for evaluation of
density / c.d.f. and quantile function of the corresponding distribution.
Most distributions of package `AbscontDistribution`

or
`DiscreteDistribution`

, which themselves are again subclasses of
`Distribution`

.
Up to arguments referring to a parameter of the distribution (like
`mean`

for the normal distribution), these function slots have the
same arguments as those of package `X`

we may call these functions as

`r(X)(n)`

}
`d(X)(x, log = FALSE)`

}
`p(X)(q, lower.tail = TRUE, log.p = FALSE)`

}
`q(X)(p, lower.tail = TRUE, log.p = FALSE)`

}
- Keywords
- package, distribution

##### Details

##### Note

Arithmetics on distribution objects are understood as operations on
corresponding (independent) r.v.'s and **not** on distribution functions
or densities.
See also `distrARITH()`

.
Some functions of package `distrMASK()`

.
Accuracy of these arithmetics is controlled by global options which may
be inspected / set by `distroptions()`

and `getdistrOption()`

,
confer distroptions .

##### code

`3*X+sin(exp(-Y/4+3))`

##### Classes

Distribution classes have a slot `param`

the class of which
is is specialized for the particualar distributions. The parameter
classes for the particular distributions have slots with names
according to the corresponding `[rdpq]` functions of
package

`AbscontDistribution`

and descendants have
a slot `gaps`

for gaps in the support.
`DiscreteDistribution`

and descendants have
an additional slot `support`

, which is again specialized
to be a lattice for class `LatticeDistribution`

.
For saved objects from earlier versions, we provide the methods
`isOldVersion`

, and `conv2NewVersion`

to check whether the object was generated by an older version of
this package and to convert such an object to the new format,
respectively. This applies to objects of subclasses of
`AbscontDistribution`

lacking a `gap`

-slot as well as to
to objects of subclasses of `LatticeDistribution`

lacking a
`lattice`

-slot.
To enhance accuracy, from version 1.9 on, we also provide
subclasses `AffLinAbscontDistribution`

, `AffLinDiscreteDistribution`

,
and `AffLinLatticeDistribution`

, as well as the class union
`AffLinDistribution`

, so that in particular functionals like `E`

from package `a`

, `b`

, and `X0`

to
reflect the fact, that a distribution object of theses classes has the
same distribution as `a*X0+b`

.
For all particular distributions, as well as for classes
`AbscontDistribution`

, `DiscreteDistribution`

,
`LatticeDistribution`

, `UnivarDistrList`

and `DistrList`

generating functions are provided, e.g. `X <- Norm(mean = 3, sd = 2)`

.
The same goes for the space classes.
All slots should be inspected / modified by means of corresponding
accessor- /replacement functions; e.g. `mean(X) <- 3`

Again to enhance accuracy, from version 2.0 on, we also provide
subclasses `UnivarMixingDistribution`

to support mixing distributions,
`UnivarLebDecDistribution`

, to support Lebesgue decomposed distributions
(with a discrete and an a.c. part) as well as `AffLinUnivarLebDecDistribution`

,
for corresponding affine linear transformations.
Class `UnivarLebDecDistribution`

is closed under arithmetical operations
+ `/`

, `*`

, `^`

for pairs of independent variables
+ `+`

, `-`

for pairs of independent variables
+ affine linear transformations
+ truncation, huberization, min/max
which are all now available analytically.
(see Parameter classes).
Distribution classes
slots: [##### Methods

The group `Math`

of unary (see Math) as well as
convolution are made available for distributions, see operators-methods;
in particular for convolution powers, we have method convpow.
Besides, there are `plot`

and `print`

-methods for distributions.
For the space classes, we have `liesIn`

, for the
`DicreteDistribution`

class, we have `liesInSupport`

, as well
as a generating function.
The "history" of distributions
obtained by chaining operations may be shortened using `simplifyr`

.

##### Functions

RtoDPQ Default procedure to fill slots d,p,q given r for a.c. distributions RtoDPQ.d Default procedure to fill slots d,p,q given r for discrete distributions RtoDPQ.LC Default procedure to fill slots d,p,q given r for Lebesgue decomposed distributions decomposePM decomposes a distribution into positive and negative part and, if discrete, into part '0' simplifyD tries to reduce/simplify mixing distribution using that certain weights are 0 flat.LCD makes a single UnivarLebDecDistribution out of a list of UnivarLebDecDistribution with corresp. weights flat.mix makes a single UnivarLebDecDistribution out of a list of a UnivarMixingDistribution distroptions Functions to change the global variables of the package 'distr' standardMethods Utility to automatically generate accessor and replacement functions

##### Acknowledgement

We thank Martin Maechler, Josef Leydold, John Chambers, Duncan Murdoch, Gregory Warnes, Paul Gilbert, Kurt Hornik, Uwe Ligges, Torsten Hothorn, and Seth Falcon for their help in preparing this package.

##### Start-up-Banner

You may suppress the start-up banner/message completely by setting
`options("StartupBanner"="off")`

somewhere before loading this
package by `library`

or `require`

in your R-code / R-session.
If option `"StartupBanner"`

is not defined (default) or setting
`options("StartupBanner"=NULL)`

or
`options("StartupBanner"="complete")`

the complete start-up banner is
displayed.
For any other value of option `"StartupBanner"`

(i.e., not in `c(NULL,"off","complete")`

)
only the version information is displayed.
The same can be achieved by wrapping the `library`

or `require`

call into either `suppressStartupMessages()`

or
`onlytypeStartupMessages(.,atypes="version")`

.
As for general `packageStartupMessage`

's, you may also suppress all
the start-up banner by wrapping the `library`

or `require`

call into `suppressPackageStartupMessages()`

from

##### Demos

Demos are available --- see `demo(package="distr")`

##### concept

- absolutely continuous distribution
- discrete distribution
- lattice distribution
- S4 classes
- arithmetics for distributions
- S4 parameter class
- S4 distribution class
- S4 space class

##### References

P. Ruckdeschel, M. Kohl, T. Stabla, F. Camphausen (2006):
S4 Classes for Distributions, {\emR News}, {\em6}(2), 2-6.
`require("distrDoc");vignette("distr")`

a small vignette on how to generate new distributions with packages `vignette("newDistributions")`

a homepage to this package is available under

##### Examples

```
X <- Unif(2,3)
Y <- Pois(lambda = 3)
Z <- X+Y # generates Law of corresponding independent variables
p(Z)(0.2)
r(Z)(1000)
plot(Z+sin(Norm()))
```

*Documentation reproduced from package distr, version 2.0.2, License: LGPL-3*