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 usedkpar
:Object of class
"list"
contains the kernel parameter usedcoef
:Object of class
"ANY"
containing the model parametersparam
:Object of class
"list"
contains the cost parameter C and tau parameter usedkcall
:Object of class
"list"
contains the used function callterms
: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 usedymatrix
:Object of class
"output"
containing the response matrixfitted
:Object of class
"output"
containing the fitted valuesalpha
:Object of class
"listI"
containing the computes alpha valuesb
:Object of class
"numeric"
containing the offset of the model.scaling
Object of class
"ANY"
containing the scaling coefficients of the data (when casescaled = TRUE
is used).error
:Object of class
"numeric"
containing the training errorcross
:Object of class
"numeric"
containing the cross validation errorn.action
:Object of class
"ANY"
containing the action performed in NAnclass
:Inherited from class
vm
, not used in kqrlev
:Inherited from class
vm
, not used in kqrtype
: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 tocoef
)- 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 (whenscaled = TRUE
is used)
Author(s)
Alexandros Karatzoglou
alexandros.karatzoglou@ci.tuwien.ac.at
See Also
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)