Dear Lurker, If all you art trying to do is to plot something, isn't all you need something like the following?
x <- c( 30, 50, 80, 90, 100) y <- c(160, 180, 250, 450, 300) sp <- spline(x, y, n = 500) plot(sp, type = "l", xlab = "x", ylab = "y", las = 1, main = "A Spline Interpolation") points(x, y, pch = 3, col = "red", lwd = 2) Bill Venables. -----Original Message----- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of e-letter Sent: Wednesday, 15 December 2010 8:37 AM To: r-help@r-project.org Subject: [R] Use generalised additive model to plot curve Readers, I have been reading 'the r book' by Crawley and think that the generalised additive model is appropriate for this problem. The package 'gam' was installed using the command (as root) install.package("gam") ... library(gam) > library(gam) Loading required package: splines Loading required package: akima > library(mgcv) This is mgcv 1.3-25 Attaching package: 'mgcv' The following object(s) are masked from package:gam : gam, gam.control, gam.fit, plot.gam, predict.gam, s, summary.gam > x<-c(30,50,80,90,100) > y<-c(160,180,250,450,300) > model<-gam(y~s(x)) Error in smooth.construct.tp.smooth.spec(object, data, knots) : A term has fewer unique covariate combinations than specified maximum degrees of freedom The objective is to plot y against x, finally to produce a graph with a smooth curve (and then remove the data points). What is my mistake please? yours, r251 gnu/linux mandriva2008 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.