colKernelSmoothing.matrix {aroma.core} | R Documentation |
Kernel smoothing of a matrix column by column
Description
Kernel smoothing of a matrix column by column.
Usage
## S3 method for class 'matrix'
colKernelSmoothing(Y, x=seq_len(nrow(Y)), w=NULL, xOut=x,
kernel=c("gaussian", "uniform"), h, censorH=3, na.rm=TRUE, robust=FALSE, ...,
verbose=FALSE)
Arguments
Y |
|
x |
A (optional) |
w |
A optional |
xOut |
A |
kernel |
A |
h |
A single positive |
censorH |
A single positive |
na.rm |
If |
robust |
If |
... |
Not used. |
verbose |
See |
Value
Returns a numeric
KxI matrix
(or a vector
of length K).
Author(s)
Henrik Bengtsson
See Also
Examples
J <- 100
I <- 4
Y <- matrix(rnorm(I*J, sd=1/2), ncol=I)
# Introduce a gain in column 2 and 3
Y[30:50,2:3] <- Y[30:50,2:3] + 3
x <- 1:J
xOut <- x
Ys1 <- colKernelSmoothing(Y, x=x, xOut=xOut, kernel="gaussian", h=1)
Ys5 <- colKernelSmoothing(Y, x=x, xOut=xOut, kernel="gaussian", h=5)
xlim <- range(c(x,xOut))
ylim <- c(-3,5)
layout(matrix(1:I, ncol=1))
par(mar=c(3,3,1,1)+0.1, pch=19)
for (ii in 1:I) {
plot(NA, xlim=xlim, ylim=ylim)
points(x, Y[,ii], col="#999999")
lines(xOut, Ys1[,ii], col=2)
points(xOut, Ys1[,ii], col=2)
lines(xOut, Ys5[,ii], col=3)
points(xOut, Ys5[,ii], col=3)
}
[Package aroma.core version 3.3.1 Index]