## simulated data... x <- runif(100) y <- rnorm(100) ## spline fit... m <- gam(y~s(x,k=6,fx=TRUE)) ## trapezoidal integration ... n <- 1000 ## number of points in trap. approx pd <- data.frame(x=seq(0,1,length=n)) dx <- pd$x[2]-pd$x[1] f <- predict.gam(m,pd) w <- rep(dx,n);w[1]<-w[n] <- w[2]/2 ## trapezoidal weights sum(w*f) ## integral
## ... same again with standard error... Xf <- predict.gam(m,pd,type="lpmatrix") t(w)%*%Xf%*%coef(m) ## integral sqrt(t(w)%*%Xf%*%m$Vp%*%t(Xf)%*%w) ## its standard error best, Simon >- Simon Wood, Mathematical Sciences, University of Bath, Bath BA2 7AY >- +44 (0)1225 386603 www.maths.bath.ac.uk/~sw283/ On Mon, 10 Apr 2006 [EMAIL PROTECTED] wrote: > > Dear R list, > > I have fitted cubic regression spline with fixed degree of freedom to a > set of data using package mgcv. Now I want to calculate the area under the > spline curve. Someone has suggested me to use trapezoidal rule. Do you know > if someone has written a package that will carry out that analysis, and > where can I download it ? > > Thanks in advance. > > > Stella > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html > ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
