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)
e1 |
object of class "Distribution" |
e2 |
object of class "Distribution" |
... |
further arguments to be used in particular methods (not in package distrEx) |
A list containing the following components:
e1 |
object of class "Distribution" ; distribution 1 |
e2 |
object of class "Distribution" ; distribution 2 |
Kolmogorov.distance |
Kolmogorov distance of e1 and e2 |
e1
and e2
.
e2
.
e1
.
Matthias Kohl Matthias.Kohl@stamats.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))