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
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
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 -
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
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)
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