scam.check | R Documentation |
Takes a fitted scam
object produced by scam()
and produces some diagnostic information
about the fitting procedure and results. This function is almost the same as gam.check
of the mgcv
library.
scam.check(b,rl.col=3,pch=".",... )
b |
a fitted |
rl.col |
color for the reference line on the quantile-quantile plot. |
pch |
plot character to use for the quantile-quantile plot. 19 is good. |
... |
extra graphics parameters to pass to plotting functions. |
As for mgcv(gam)
plots 4 standard diagnostic plots, and some other
convergence diagnostics. The
printed information relates to the optimization process used to select smoothing
parameters.
Natalya Pya <nat.pya@gmail.com> based partly on mgcv
by Simon Wood
Wood S.N. (2006) Generalized Additive Models: An Introduction with R. Chapman and Hall/CRC Press.
scam
## Not run:
library(scam)
set.seed(2)
n <- 200
x1 <- runif(n)*4-1;
f1 <- exp(4*x1)/(1+exp(4*x1)) # monotone increasing smooth
x2 <- runif(n)*3-1;
f2 <- exp(-3*x2)/15 # monotone decreasing and convex smooth
f <- f1+f2
y <- f+ rnorm(n)*0.2
dat <- data.frame(x1=x1,x2=x2,y=y)
b <- scam(y~ s(x1,k=25,bs="mpi",m=2)+s(x2,k=25,bs="mdcx",m=2),
family=gaussian(link="identity"),data=dat)
plot(b,pages=1)
scam.check(b,pch=19,cex=.3)
## End(Not run)
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