simplifyD-methods

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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

Huberize, Minimum

Aliases
  • simplifyD-methods
  • simplifyD
  • simplifyD,AbscontDistribution-method
  • simplifyD,DiscreteDistribution-method
  • simplifyD,UnivarLebDecDistribution-method
  • simplifyD,UnivarMixingDistribution-method
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 2.8.0, License: LGPL-3

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