| Minimum-methods {distr} | R Documentation |
Minimum and Maximum-methods
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"))
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? |
the corresponding distribution of the minimum / maximum
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"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"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"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"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"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"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"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()))