# kmmd-class

##### Class "kqr"

The Kernel Maximum Mean Discrepancy object class

- Keywords
- classes

##### 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

```
# NOT RUN {
# create data
x <- matrix(runif(300),100)
y <- matrix(runif(300)+1,100)
mmdo <- kmmd(x, y)
H0(mmdo)
# }
```

*Documentation reproduced from package kernlab, version 0.9-27, License:*