kernlab (version 0.9-24)

kmmd-class: Class "kqr"

Description

The Kernel Maximum Mean Discrepancy object class

Arguments

Objects from the Class

Objects can be created by calls of the form new("kmmd", ...). or by calling the kmmd function

Slots

kernelf:
Object of class "kfunction" contains the kernel function used
xmatrix:
Object of class "kernelMatrix" containing the data used
H0
Object of class "logical" contains value of : is H0 rejected (logical)
AsympH0
Object of class "logical" contains value : is H0 rejected according to the asymptotic bound (logical)
mmdstats
Object of class "vector" contains the test statistics (vector of two)
Radbound
Object of class "numeric" contains the Rademacher bound
Asymbound
Object of class "numeric" contains the asymptotic bound

Methods

kernelf
signature(object = "kmmd"): returns the kernel function used
H0
signature(object = "kmmd"): returns the value of H0 being rejected
AsympH0
signature(object = "kmmd"): returns the value of H0 being rejected according to the asymptotic bound
mmdstats
signature(object = "kmmd"): returns the values of the mmd statistics
Radbound
signature(object = "kmmd"): returns the value of the Rademacher bound
Asymbound
signature(object = "kmmd"): returns the value of the asymptotic bound

See Also

kmmd,

Examples

Run this code
# create data
x <- matrix(runif(300),100)
y <- matrix(runif(300)+1,100)


mmdo <- kmmd(x, y)

H0(mmdo)

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