Last data update: 2014.03.03
R: Class "kqr"
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)
Results