KolmogorovDist {distrEx} | R Documentation |
Generic function for the computation of the Kolmogorov distance d_k of two distributions P and Q where the distributions are defined on a finite-dimensional Euclidean space (R^m, B^m) with B^m the Borel-sigma-algebra on R^m. The Kolmogorov distance is defined as
d_k(P,Q)=sup{|P({y in R^m | y <= x})-Q({y in R^m | y <= x})| | x in R^m}
where <= is coordinatewise on R^m.
KolmogorovDist(e1, e2, ...) ## S4 method for signature 'AbscontDistribution, ## AbscontDistribution': KolmogorovDist(e1,e2) ## S4 method for signature 'AbscontDistribution, ## DiscreteDistribution': KolmogorovDist(e1,e2) ## S4 method for signature 'DiscreteDistribution, ## AbscontDistribution': KolmogorovDist(e1,e2) ## S4 method for signature 'DiscreteDistribution, ## DiscreteDistribution': KolmogorovDist(e1,e2) ## S4 method for signature 'numeric, ## UnivariateDistribution': KolmogorovDist(e1, e2) ## S4 method for signature 'UnivariateDistribution, ## numeric': KolmogorovDist(e1, e2) ## S4 method for signature 'AcDcLcDistribution, ## AcDcLcDistribution': KolmogorovDist(e1, e2)
e1 |
object of class "Distribution" or class "numeric" |
e2 |
object of class "Distribution" or class "numeric" |
... |
further arguments to be used in particular methods (not in package distrEx) |
Kolmogorov distance of e1
and e2
e1
and e2
.
e2
.
e1
.
ks.test
.
ks.test
.
e1
.
Matthias Kohl Matthias.Kohl@stamats.de,
Peter Ruckdeschel Peter.Ruckdeschel@itwm.fraunhofer.de
Huber, P.J. (1981) Robust Statistics. New York: Wiley.
Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.
ContaminationSize
, TotalVarDist
,
HellingerDist
, Distribution-class
KolmogorovDist(Norm(), Gumbel()) KolmogorovDist(Norm(), Td(10)) KolmogorovDist(Norm(mean = 50, sd = sqrt(25)), Binom(size = 100)) KolmogorovDist(Pois(10), Binom(size = 20)) KolmogorovDist(Norm(), rnorm(100)) KolmogorovDist((rbinom(50, size = 20, prob = 0.5)-10)/sqrt(5), Norm()) KolmogorovDist(rbinom(50, size = 20, prob = 0.5), Binom(size = 20, prob = 0.5))