R: Class "kqr"

kqr-class {kernlab} | R Documentation

## Class "kqr"

### Description

The Kernel Quantile Regression object class

### Objects from the Class

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

### Slots

`kernelf`:

  Object of class `"kfunction"` contains the kernel function used

`kpar`:

  Object of class `"list"` contains the kernel parameter used

`coef`:

  Object of class `"ANY"` containing the model parameters

`param`:

  Object of class `"list"` contains the cost parameter C and tau parameter used

`kcall`:

  Object of class `"list"` contains the used function call

`terms`:

  Object of class `"ANY"` contains the terms representation of the symbolic model used (when using a formula)

`xmatrix`:

  Object of class `"input"` containing the data matrix used

`ymatrix`:

  Object of class `"output"` containing the response matrix

`fitted`:

  Object of class `"output"` containing the fitted values

`alpha`:

  Object of class `"listI"` containing the computes alpha values

`b`:

  Object of class `"numeric"` containing the offset of the model.

`scaling`

  Object of class `"ANY"` containing the scaling coefficients of the data (when case `scaled = TRUE` is used).

`error`:

  Object of class `"numeric"` containing the training error

`cross`:

  Object of class `"numeric"` containing the cross validation error

`n.action`:

  Object of class `"ANY"` containing the action performed in NA

`nclass`:

  Inherited from class `vm`, not used in kqr

`lev`:

  Inherited from class `vm`, not used in kqr

`type`:

  Inherited from class `vm`, not used in kqr

### Methods

coef

  `signature(object = "kqr")`: returns the coefficients (alpha) of the model

alpha

  `signature(object = "kqr")`: returns the alpha vector (identical to `coef`)

b

  `signature(object = "kqr")`: returns the offset beta of the model.

cross

  `signature(object = "kqr")`: returns the cross validation error

error

  `signature(object = "kqr")`: returns the training error

fitted

  `signature(object = "vm")`: returns the fitted values

kcall

  `signature(object = "kqr")`: returns the call performed

kernelf

  `signature(object = "kqr")`: returns the kernel function used

kpar

  `signature(object = "kqr")`: returns the kernel parameter used

param

  `signature(object = "kqr")`: returns the cost regularization parameter C and tau used

xmatrix

  `signature(object = "kqr")`: returns the data matrix used

ymatrix

  `signature(object = "kqr")`: returns the response matrix used

scaling

  `signature(object = "kqr")`: returns the scaling coefficients of the data (when `scaled = TRUE` is used)

### Author(s)

Alexandros Karatzoglou
alexandros.karatzoglou@ci.tuwien.ac.at

### See Also

`kqr`, `vm-class`, `ksvm-class`

### Examples

    # create data
    x <- sort(runif(300))
    y <- sin(pi*x) + rnorm(300,0,sd=exp(sin(2*pi*x)))

    # first calculate the median
    qrm <- kqr(x, y, tau = 0.5, C=0.15)

    # predict and plot
    plot(x, y)
    ytest <- predict(qrm, x)
    lines(x, ytest, col="blue")

    # calculate 0.9 quantile
    qrm <- kqr(x, y, tau = 0.9, kernel = "rbfdot",
               kpar = list(sigma = 10), C = 0.15)
    ytest <- predict(qrm, x)
    lines(x, ytest, col="red")

    # print model coefficients and other information
    coef(qrm)
    b(qrm)
    error(qrm)
    kernelf(qrm)

[Package kernlab version 0.9-25 Index]