Minimummethods {distr}  R Documentation 
Methods for functions Minimum and Maximum in Package ‘distr’
Description
Minimum and Maximummethods
Usage
Minimum(e1, e2, ...)
Maximum(e1, e2, ...)
## S4 method for signature 'AbscontDistribution,AbscontDistribution'
Minimum(e1,e2, ...)
## S4 method for signature 'DiscreteDistribution,DiscreteDistribution'
Minimum(e1,e2, ...)
## S4 method for signature 'AbscontDistribution,Dirac'
Minimum(e1,e2,
withSimplify = getdistrOption("simplifyD"))
## S4 method for signature 'AcDcLcDistribution,AcDcLcDistribution'
Minimum(e1,e2,
withSimplify = getdistrOption("simplifyD"))
## S4 method for signature 'AcDcLcDistribution,AcDcLcDistribution'
Maximum(e1,e2,
withSimplify = getdistrOption("simplifyD"))
## S4 method for signature 'AbscontDistribution,numeric'
Minimum(e1,e2, ...)
## S4 method for signature 'DiscreteDistribution,numeric'
Minimum(e1,e2, ...)
## S4 method for signature 'AcDcLcDistribution,numeric'
Minimum(e1,e2,
withSimplify = getdistrOption("simplifyD"))
## S4 method for signature '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

Value
the corresponding distribution of the minimum / maximum
Methods
 Minimum
signature(e1 = "AbscontDistribution", e2 = "AbscontDistribution")
: returns the distribution ofmin(X1,X2)
, ifX1
,X2
are independent and distributed according toe1
ande2
respectively; the result is again of class"AbscontDistribution"
 Minimum
signature(e1 = "DiscreteDistribution", e2 = "DiscreteDistribution")
: returns the distribution ofmin(X1,X2)
, ifX1
,X2
are independent and distributed according toe1
ande2
respectively; the result is again of class"DiscreteDistribution"
 Minimum
signature(e1 = "AbscontDistribution", e2 = "Dirac")
: returns the distribution ofmin(X1,X2)
, ifX1
,X2
are distributed according toe1
ande2
respectively; the result is of class"UnivarLebDecDistribution"
 Minimum
signature(e1 = "AcDcLcDistribution", e2 = "AcDcLcDistribution")
: returns the distribution ofmin(X1,X2)
, ifX1
,X2
are distributed according toe1
ande2
respectively; the result is of class"UnivarLebDecDistribution"
 Minimum
signature(e1 = "AcDcLcDistribution", e2 = "numeric")
: ife2
=n
, returns the distribution ofmin(X1,X2,...,Xn)
, ifX1
,X2
, ...,Xn
are i.i.d. according toe1
; the result is of class"UnivarLebDecDistribution"
 Maximum
signature(e1 = "AcDcLcDistribution", e2 = "AcDcLcDistribution")
: returns the distribution ofmax(X1,X2)
, ifX1
,X2
are distributed according toe1
ande2
respectively; translates intoMinimum(e1,e2)
; the result is of class"UnivarLebDecDistribution"
 Maximum
signature(e1 = "AcDcLcDistribution", e2 = "numeric")
: ife2
=n
, returns the distribution ofmax(X1,X2,...,Xn)
, ifX1
,X2
, ...,Xn
are i.i.d. according toe1
; translates intoMinimum(e1,e2)
; the result is of class"UnivarLebDecDistribution"
See Also
Examples
## IGNORE_RDIFF_BEGIN
plot(Maximum(Unif(0,1), Minimum(Unif(0,1), Unif(0,1))))
plot(Minimum(Exp(4),4))
## IGNORE_RDIFF_END
## a sometimes lengthy example...
plot(Minimum(Norm(),Pois()))