R help - Nov 2013 - Fitting arbitrary curve to 1D data with error bars

Dear R experts,

I was wondering how I could do a fit (say minimum chi2) to a 1D data with error
bars. I searched quite a lot on the web, found out about the fitdistr() function
in MASS, etc., but none of the things I found gives what I am really looking
for. Perhaps I do not exactly know the proper terminology and this is why I
cannot find the solution. We could also probably describe it as "parameter
estimation using the minimum chi2 method using data with error bars and an
arbitrary fitting function".

Anyway, in order not to confuse people with possibly incorrect terminology, let
me show you what I am really looking for. Here is a page that shows what I want
in Matlab (see the section on weighted fit):

http://www.mathworks.com/matlabcentral/fileexchange/10176-ezyfit-2-41/content/ezyfit/demo/html/efdemo.html#19

Could you please help?

Thanks in advance,
e.


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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)