R: Methods for functions Minimum and Maximum in Package 'distr'

Minimum-methods {distr} | R Documentation

## Methods for functions Minimum and Maximum in Package ‘distr’

### Description

Minimum and Maximum-methods

### 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 `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`

### Examples

    plot(Maximum(Unif(0,1), Minimum(Unif(0,1), Unif(0,1))))
    plot(Minimum(Exp(4),4))
    ## a sometimes lengthy example...
    plot(Minimum(Norm(),Pois()))

[Package distr version 2.8.0 Index]