JOPS (version 0.2.0)

plot.pssignal: Plotting function for psSignal

Description

Plotting function for signal regression P-spline smooth coefficients (using psSignal with class pssignal), with or without standard error bands.

Usage

# S3 method for pssignal
plot(x, ..., se = 2, xlab = "", ylab = "", col = "black", lty = 1)

Value

Plot

a plot of the smooth P-spline signal coefficent vector, with or without standard error bands.

Arguments

x

the P-spline x, usually from psSignal.

...

other parameters.

se

a scalar, e.g. se = 2 to produce twice se bands, set se > 0 (or set se = 0 to supress).

xlab

label for the x-axis, e.g. "my x" (quotes required).

ylab

label for the y-axis, e.g. "my y" (quotes required).

col

color.

lty

line type for plotting e.g. lty = 2.

Author

Paul Eilers and Brian Marx

References

Marx, B.D. and Eilers, P.H.C. (1999). Generalized linear regression for sampled signals and curves: A P-spline approach. Technometrics, 41(1): 1-13.

Eilers, P.H.C. and Marx, B.D. (2021). Practical Smoothing, The Joys of P-splines. Cambridge University Press.

Examples

library(JOPS)
# Get the data
library(fds)
data(nirc)
iindex=nirc$x
X=nirc$y
sel= 50:650 #1200 <= x & x<= 2400
X=X[sel, ]
iindex=iindex[sel]
dX=diff(X)
diindex=iindex[-1]
y=as.vector(labc[1,1:40])
oout = 23
dX=t(dX[,-oout])
y=y[-oout]
fit2 = psSignal(y, dX, diindex, nseg = 25,lambda = 0.0001)
plot(fit2, se = 2, xlab = 'Coefficient Index', ylab= "ps Smooth Coeff")
title(main='25 B-spline segments with tuning=0.0001')
names(fit2)