Thanks, this was a useful pointer. Since the function I am trying to fit is exponential, I decided to use nls. And I was able to reproduce exactly the results and the plot in the URL I had posted. For future reference, here is the R code I wrote:
require("gplots") xx <- 1:10 yy <- c(1.56,1.20,1.10,0.74,0.57,0.55,0.31,0.27,0.28,0.11) dy <- c(0.02,0.02,0.20,0.03,0.03,0.10,0.05,0.02,0.10,0.05) plotCI(xx,yy,uiw=dy,gap=0) nlmod <- nls(yy ~ Alpha * exp(Beta * xx), start=list(Alpha=1, Beta=-1)) lines(xx, predict(nlmod), col = "blue") wnlmod <- nls(yy ~ Alpha * exp(Beta * xx), start=list(Alpha=1, Beta=-1), weights=dy^-2) lines(xx, predict(wnlmod), col = "red") Thanks to everybody who responded, e. On 14 Nov 2013, at 11:34, Suzen, Mehmet wrote: > Maybe you are after "weights" option given by 'lm' or 'glm' > > See: > http://stackoverflow.com/questions/6375650/function-for-weighted-least-squares-estimates > > On 14 November 2013 10:01, Erkcan Özcan <erk...@hotmail.com> wrote: >> Thanks, but if you have another closer look to my post, you will see that my >> question has nothing to do with drawing error bars on a plot. >> >> What I want is to do a curve fit to a data with error bars. >> >> Best, >> e. >> >> On 14 Nov 2013, at 04:21, Suzen, Mehmet wrote: >> >>> If you are after adding error bars in a scatter plot; one example is >>> given below : >>> >>> #some example data >>> set.seed(42) >>> df <- data.frame(x = rep(1:10,each=5), y = rnorm(50)) >>> >>> #calculate mean, min and max for each x-value >>> library(plyr) >>> df2 <- ddply(df,.(x),function(df) >>> c(mean=mean(df$y),min=min(df$y),max=max(df$y))) >>> >>> #plot error bars >>> library(Hmisc) >>> with(df2,errbar(x,mean,max,min)) >>> grid(nx=NA,ny=NULL) >>> >>> (From: >>> http://stackoverflow.com/questions/13032777/scatter-plot-with-error-bars) >>> >> > ______________________________________________ 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.