Description Usage Arguments Details Author(s) See Also Examples
Plotting a unimodal regression object into an existing plot.
1 2 |
x |
Object of class |
type |
Per default plotting type |
... |
other parameters to be passed through to the generic |
This is a points method for unimodal regression objects. The spline function is plotted using a grid of x-values equally spaced across the interval on which the spline is defined. The distance between the grid values is given by the minimal distance of the observed x-values (used for fitting) divided by 10.
Claudia Koellmann
unireg
,predict.unireg
,plot.unireg
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | x <- sort(rep(0:5,20))
n <- length(x)
set.seed(41333)
func <- function(mu){rnorm(1,mu,0.05)}
y <- sapply(dchisq(x,3),func)
# plot of data
plot(jitter(x), y, xlab="x (jittered)")
# fit with default settings
fit <- unireg(x, y, g=5)
# short overview of the fitted spline
fit
# plot of true and fitted functions
plot(jitter(x), y, xlab="x (jittered)")
curve(dchisq(x,3), 0, 5, type="l", col="grey", lwd=2, add=TRUE)
points(fit, lwd=2, col="orange")
legend("bottomright", legend = c("true mean function",
"difference penalized unimodal fit"),
col=c("grey","orange"),lwd=c(2,2))
|
Fitted unimodal spline of degree 3 with difference penalty of order 2
Coefficients -0.21 0.03 0.23 0.23 0.18 0.13 0.09 0.07 0.05
Mode of coefficients 3 4
Tuning parameter 20.09
Variance estimate 0
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