CvMDist {distrEx} | R Documentation |
Generic function for the computation of the Cramer - von Mises distance d_{mu} 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 Cramer - von Mises distance is defined as
d_{mu}(P,Q)^2=int (P({y in R^m | y <= x})-Q({y in R^m | y <= x}))^2 mu(dx)
where <= is coordinatewise on R^m.
CvMDist(e1, e2, ...) ## S4 method for signature 'UnivariateDistribution, ## UnivariateDistribution': CvMDist(e1, e2, mu = e2, useApply = FALSE, ...) ## S4 method for signature 'numeric, ## UnivariateDistribution': CvMDist(e1, e2, mu = e2, ...)
e1 |
object of class "Distribution" or class "numeric" |
e2 |
object of class "Distribution" |
... |
further arguments to be used e.g. by E() |
useApply |
logical; to be passed to E() |
mu |
object of class "Distribution" ; integration measure; defaulting to e2 |
Cramer - von Mises distance of e1
and e2
Matthias Kohl Matthias.Kohl@stamats.de,
Peter Ruckdeschel Peter.Ruckdeschel@itwm.fraunhofer.de
Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.
ContaminationSize
, TotalVarDist
,
HellingerDist
, KolmogorovDist
,
Distribution-class
CvMDist(Norm(), Gumbel()) CvMDist(Norm(), Gumbel(), mu = Norm()) CvMDist(Norm(), Td(10)) CvMDist(Norm(mean = 50, sd = sqrt(25)), Binom(size = 100)) CvMDist(Pois(10), Binom(size = 20)) CvMDist(rnorm(100),Norm()) CvMDist((rbinom(50, size = 20, prob = 0.5)-10)/sqrt(5), Norm()) CvMDist(rbinom(50, size = 20, prob = 0.5), Binom(size = 20, prob = 0.5)) CvMDist(rbinom(50, size = 20, prob = 0.5), Binom(size = 20, prob = 0.5), mu = Pois())