HellingerDist {distrEx} | R Documentation |
Generic function for the computation of the Hellinger distance d_h of two distributions P and Q which may be defined for an arbitrary sample space (Omega, A). The Hellinger distance is defined as
0.5 int |sqrt{dP}-sqrt{dQ}|^2
where sqrt{dP}, respectively sqrt{dQ} denotes the square root of the densities.
HellingerDist(e1, e2, ...) ## S4 method for signature 'AbscontDistribution, ## AbscontDistribution': HellingerDist(e1,e2) ## S4 method for signature 'AbscontDistribution, ## DiscreteDistribution': HellingerDist(e1,e2) ## S4 method for signature 'DiscreteDistribution, ## AbscontDistribution': HellingerDist(e1,e2) ## S4 method for signature 'DiscreteDistribution, ## DiscreteDistribution': HellingerDist(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 |
Hellinger.distance |
Hellinger distance of e1 and e2 |
distrExintegrate
.
=1
).support
and sum
.
=1
).Matthias Kohl Matthias.Kohl@stamats.de
Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.
distrExIntegrate
, ContaminationSize
,
TotalVarDist
, KolmogorovDist
,
Distribution-class
HellingerDist(Norm(), Gumbel()) HellingerDist(Norm(), Td(10)) HellingerDist(Norm(mean = 50, sd = sqrt(25)), Binom(size = 100)) # mutually singular HellingerDist(Pois(10), Binom(size = 20))