predict.kqr: Predict method for kernel Quantile Regression object

In elad663/kernlab: Kernel-Based Machine Learning Lab

Description

Prediction of test data for kernel quantile regression

Usage

## S4 method for signature 'kqr'
predict(object, newdata)

Arguments

object	an S4 object of class kqr created by the kqr function
newdata	a data frame, matrix, or kernelMatrix containing new data

Value

The value of the quantile given by the computed kqr model in a vector of length equal to the the rows of newdata.

Author(s)

Alexandros Karatzoglou
[e-mail]

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")

elad663/kernlab documentation built on May 7, 2019, 6:06 a.m.