Minimum-methods

0th

Percentile

Methods for functions Minimum and Maximum in Package `distr'

Minimum and Maximum-methods

Keywords
methods, distribution
Usage
Minimum(e1, e2, ...)
Maximum(e1, e2, ...) 
# S4 method for AbscontDistribution,AbscontDistribution
Minimum(e1,e2, ...)
# S4 method for DiscreteDistribution,DiscreteDistribution
Minimum(e1,e2, ...)
# S4 method for AbscontDistribution,Dirac
Minimum(e1,e2, 
                   withSimplify = getdistrOption("simplifyD"))
# S4 method for AcDcLcDistribution,AcDcLcDistribution
Minimum(e1,e2, 
                   withSimplify = getdistrOption("simplifyD"))
# S4 method for AcDcLcDistribution,AcDcLcDistribution
Maximum(e1,e2, 
                   withSimplify = getdistrOption("simplifyD"))
# S4 method for AbscontDistribution,numeric
Minimum(e1,e2, ...)
# S4 method for DiscreteDistribution,numeric
Minimum(e1,e2, ...)
# S4 method for AcDcLcDistribution,numeric
Minimum(e1,e2,
                   withSimplify = getdistrOption("simplifyD"))
# S4 method for AcDcLcDistribution,numeric
Maximum(e1,e2, 
                   withSimplify = getdistrOption("simplifyD"))
Arguments
e1

distribution object

e2

distribution object or numeric

further arguments (to be able to call various methods with the same arguments

withSimplify

logical; is result to be piped through a call to simplifyD?

Value

the corresponding distribution of the minimum / maximum

Methods

Minimum

signature(e1 = "AbscontDistribution", e2 = "AbscontDistribution"): returns the distribution of min(X1,X2), if X1,X2 are independent and distributed according to e1 and e2 respectively; the result is again of class "AbscontDistribution"

Minimum

signature(e1 = "DiscreteDistribution", e2 = "DiscreteDistribution"): returns the distribution of min(X1,X2), if X1,X2 are independent and distributed according to e1 and e2 respectively; the result is again of class "DiscreteDistribution"

Minimum

signature(e1 = "AbscontDistribution", e2 = "Dirac"): returns the distribution of min(X1,X2), if X1,X2 are distributed according to e1 and e2 respectively; the result is of class "UnivarLebDecDistribution"

Minimum

signature(e1 = "AcDcLcDistribution", e2 = "AcDcLcDistribution"): returns the distribution of min(X1,X2), if X1,X2 are distributed according to e1 and e2 respectively; the result is of class "UnivarLebDecDistribution"

Minimum

signature(e1 = "AcDcLcDistribution", e2 = "numeric"): if e2 = \(n\), returns the distribution of min(X1,X2,...,Xn), if X1,X2, ..., Xn are i.i.d. according to e1; the result is of class "UnivarLebDecDistribution"

Maximum

signature(e1 = "AcDcLcDistribution", e2 = "AcDcLcDistribution"): returns the distribution of max(X1,X2), if X1,X2 are distributed according to e1 and e2 respectively; translates into -Minimum(-e1,-e2); the result is of class "UnivarLebDecDistribution"

Maximum

signature(e1 = "AcDcLcDistribution", e2 = "numeric"): if e2 = \(n\), returns the distribution of max(X1,X2,...,Xn), if X1,X2, ..., Xn are i.i.d. according to e1; translates into -Minimum(-e1,e2); the result is of class "UnivarLebDecDistribution"

See Also

Huberize, Truncate

Aliases
  • Minimum-methods
  • Minimum
  • Maximum-methods
  • Maximum
  • Minimum,AbscontDistribution,AbscontDistribution-method
  • Minimum,DiscreteDistribution,DiscreteDistribution-method
  • Minimum,AbscontDistribution,Dirac-method
  • Minimum,AcDcLcDistribution,AcDcLcDistribution-method
  • Minimum,AbscontDistribution,numeric-method
  • Minimum,DiscreteDistribution,numeric-method
  • Minimum,AcDcLcDistribution,numeric-method
  • Maximum,AcDcLcDistribution,AcDcLcDistribution-method
  • Maximum,AcDcLcDistribution,numeric-method
Examples
# NOT RUN {
plot(Maximum(Unif(0,1), Minimum(Unif(0,1), Unif(0,1))))
plot(Minimum(Exp(4),4))
## a sometimes lengthy example...
# }
# NOT RUN {
plot(Minimum(Norm(),Pois()))
# }
Documentation reproduced from package distr, version 2.8.0, License: LGPL-3

Community examples

Looks like there are no examples yet.