# EmpiricalDistribution

##### Generating function "EmpiricalDistribution"

Generates an object of class `"DiscreteDistribution"`

- Keywords
- distribution

##### Usage

```
EmpiricalDistribution(data, .withArith=FALSE, .withSim=FALSE,
.lowerExact = TRUE, .logExact = FALSE,
.DistrCollapse = getdistrOption("DistrCollapse"),
.DistrCollapse.Unique.Warn =
getdistrOption("DistrCollapse.Unique.Warn"),
.DistrResolution = getdistrOption("DistrResolution"),
Symmetry = NoSymmetry())
```

##### Arguments

- data
numeric vector with data.

- .withArith
normally not set by the user, but if determining the entries

`supp`

,`prob`

distributional arithmetics was involved, you may set this to`TRUE`

.- .withSim
normally not set by the user, but if determining the entries

`supp`

,`prob`

simulations were involved, you may set this to`TRUE`

.- .lowerExact
normally not set by the user: whether the

`lower.tail=FALSE`

part is calculated exactly, avoing a ```1-.`

''.- .logExact
normally not set by the user: whether in determining slots

`d,p,q`

, we make particular use of a logarithmic representation to enhance accuracy.- .DistrCollapse
controls whether in generating a new discrete distribution, support points closer together than

`.DistrResolution`

are collapsed.- .DistrCollapse.Unique.Warn
controls whether there is a warning whenever collapsing occurs or when two points are collapsed by a call to

`unique()`

(default behaviour if`.DistrCollapse`

is`FALSE`

)- .DistrResolution
minimal spacing between two mass points in a discrete distribution

- Symmetry
you may help R in calculations if you tell it whether the distribution is non-symmetric (default) or symmetric with respect to a center; in this case use

`Symmetry=SphericalSymmetry(center)`

.

##### Details

The function is a simple utility function providing a wrapper to the
generating function `DiscreteDistribution`

.

Typical usage is

EmpiricalDistribution(data)

##### Value

Object of class `"DiscreteDistribution"`

##### See Also

##### Examples

```
# NOT RUN {
x <- rnorm(20)
D1 <- EmpiricalDistribution(data = x)
D1
plot(D1)
# }
```

*Documentation reproduced from package distr, version 2.7.0, License: LGPL-3*