panel.pspline: Panel function for adding a P-spline smoothed curves to a...

In TurboNorm: A fast scatterplot smoother suitable for microarray normalization

Description

The function panel.pspline is similar to panel.loess but show the P-spline smoothed curve.

Usage

panel.pspline(x, y, weights = rep(1, length(y)), nintervals = 100, type, horizontal = FALSE, col.line=1, lty=1, lwd=1, ...)

Arguments

x, y	vectors giving the coordinates of the points in the scatter plot
weights	vector of weights of with same length as the data for a weighted smoothing. Default all weights are 1.
nintervals	an integer indicating the number of intervals equal to 1 + number of knots. Currently the intervals must be langer than 10.
type	see panel.loess
horizontal	see panel.loess
col.line, lty, lwd	line colour, type and width that will be used in the plots, defaults are col=1, lty=1 and lwd=1.
...	see panel.loess

Details

?panel.loess

Author(s)

Maarten van Iterson and Chantal van Leeuwen

References

Deepayan Sarkar (2009). lattice: Lattice Graphics. R package version 0.17-26. http://CRAN.R-project.org/package=lattice

van Iterson M, Duijkers FA, Meijerink JP, Admiraal P, van Ommen GJ, Boer JM, van Noesel MM, Menezes RX (2012). A novel and fast normalization method for high-density arrays. SAGMB, 11(4).

Paul .H.C. Eilers and Brain D. Marx (1996). Flexible smoothing with B-splines and Penalties. Statistical Science, Vol 11, No. 2, 89-121.

See Also

panel.loess

Examples

library(marray)
library(lattice)
data(swirl)
data <- data.frame(M=as.vector(maM(swirl)), A=as.vector(maA(swirl)), Sample=rep(paste("Array", 1:4), each=nrow(swirl)))

xyplot(M~A|Sample, data=data,
                        panel = function(x, y) {
            panel.grid(h=-1, v= 2)
            panel.xyplot(x, y)
            panel.loess(x, y, span=0.25, col="black")
                                                panel.pspline(x, y, col="red", lwd=2)})

TurboNorm documentation built on Nov. 8, 2020, 6:46 p.m.