Hello, I have a question regarding shading regions under curves to display 95% confidence intervals. I generated bootstrap results for the slope and intercept of a simple linear regression model using the following code (borrowed from JJ Faraway 2005):
> attach(allposs.nine.d) > x<-model.matrix(~log(d.dist,10))[,-1] > bcoef<-matrix(0,1000,2) > for(i in 1:1000){ + newy<-predict(all.d.nine.lm)+residuals(all.d.nine.lm)[sample(1002,rep=TRUE)] + brg<-lm(newy~x) + bcoef[i,]<-brg$coef + } Where "allposs.nine.d" is a data file composed of two columns: (1) geographical distances between sample points ("d.dist") and (2) their respective pairwise percent similarity in species composition ("d.sim"). The expression "all.d.nine.lm" equals lm(d.sim~d.dist). I saved the bootstrap results for each coefficient as: > dist.density.b1<-density(bcoef[,2]) > dist.density.b0<-density(bcoef[,1]) Along with their 95% confidence intervals: > dist.quant.b1<-quantile(bcoef[,2],c(.025,.975)) > dist.quant.b0<-quantile(bcoef[,1],c(.025,.975)) I then could plot smooth density curves along with their 95% CI's: > plot(dist.density.b1) > abline(v=dist.quant.b1) Now finally for my question: Instead of drawing vertical lines to represent the 95% CI's, I'd much prefer to somehow shade in the region under the curve corresponding the to 95% CI. I tried using the polygon() function for this but did not get very far as I couldn't figure out how to define limits for x and y coordinates. Any suggestions would be great. Thanks very much-- Andy Romigner ______________________________________________ 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.