# simplifyD-methods

##### Methods for function simplifyD in Package `distr'

simplifyD-methods

- Keywords
- methods, distribution

##### Usage

`simplifyD(object)`

##### Arguments

- object
distribution object

##### Details

generating functions `UnivarMixingDistribution`

`Minimum`

, `Maximum`

, `Truncate`

, and
`Huberize`

have an argument `withSimplify`

which
decides whether the respective result is filtered by/piped through a
call to `simplifyD`

.
By default this argument is set to the distr-option
`getdistrOption("simplifyD"`

(for the inspection and modification of such
global options see `distroptions`

). Depending on whether or not this
option is `TRUE`

, also arithmetic operations `"+"`

, `"*"`

, `"/"`

,
`"^"`

and group `Math`

give results filtered by/piped through a call
to `simplifyD`

.

##### Value

the corresponding, possibly simplified distribution

##### Methods

- simplifyD
`signature(object = "AbscontDistribution")`

: returns`object`

unchanged- simplifyD
`signature(object = "DiscreteDistribution")`

: returns`object`

unchanged- simplifyD
`signature(object = "UnivarLebDecDistribution")`

: checks whether`acWeight`

or`discreteWeight`

is approximately (i.e.; up to`getdistrOption("TruncQuantile")`

) zero and if so, accordingly returns`discretePart(object)`

or`acPart(object)`

, respectively.- simplifyD
`signature(object = "UnivarMixingDistribution")`

: returns the flattened version of`object`

(using`flat.mix`

). before doing so, it checks whether any component carries weight approximately (i.e.; up to`getdistrOption("TruncQuantile")`

) one (in slot`mixCoeff`

) and if so, returns this component; else, if not all weights are below`getdistrOption("TruncQuantile")`

), it filters out those components with weight less than`getdistrOption("TruncQuantile")`

).

##### See Also

##### Examples

```
# NOT RUN {
set.seed(123)
Mix1 <- UnivarMixingDistribution(Norm(),Binom(2,.3),
UnivarLebDecDistribution(acPart = Chisq(df = 2), discretePart = Nbinom(3,.09),
acWeight = 0.3),
Norm()-Chisq(df=3), mixCoeff=c(0,0,0.2,0.8), withSimplify = FALSE)
Mix2 <- UnivarMixingDistribution(Norm(),Mix1, DExp(2),
mixCoeff = c(0,0.2,0.8), withSimplify = FALSE)
Mix2
simplifyD(Mix2)
# }
```

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