Try using the function in the plyr package. E.g.,
> z <- data.frame( # your toy dataset
run = c(1, 2, 1, 2),
par = c(10, 10, 20, 20),
measured = c(12, 14, 20, 26))
> library(plyr)
> ddply(z, .(par), summarize, meanMeasured=mean(measured),
sdMeasured=sd(measured))
par meanMeasured sdMeasured
1 10 13 1.414214
2 20 23 4.242641
Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com
> -----Original Message-----
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
> Behalf Of Ireneusz
> Szczesniak
> Sent: Tuesday, January 17, 2012 2:43 PM
> To: r-help@r-project.org
> Subject: Re: [R] Mean of simulation runs given in a table
>
> Thank you, Uwe, for your help! I have more measurements (m1, m2) and
> more parameters (par1, par2). I can calculate the means of m1 and m2
> this way:
>
> aggregate(cbind(m1, m2) ~ par1 + par2, dat, mean)
>
> However, I also need to calculate the standard error of the mean, and
> the variance for the sample, and I would like to have them output as
> extra columns next to the column with means.
>
> Again, I would appreciate any help!
>
> On 17.01.2012 15:09, Uwe Ligges wrote:
> >
> >
> > On 17.01.2012 12:31, Irek Szczesniak wrote:
> >> Hi,
> >>
> >> I have the simulation results of the following structure:
> >>
> >> run par measured
> >> 1 10 12
> >> 2 10 14
> >> 1 20 20
> >> 2 20 26
> >>
> >> Where "run" is the simulation run number, "par" is the parameter of
> >> the simulation, and "measured" is the value measured in the
> >> simulation. This is only a simple example of my results. There are
> >> many values measured and many parameters. But the basic structure
> >> stays the same: there are many runs (identified by the run number) for
> >> the same values of the parameters with various measured values -- they
> >> constitute a sample.
> >>
> >> I would like to calculate the mean of the "measured" value for a
> >> sample, and so I would like to obtain the output as follows:
> >>
> >> par mean
> >> 10 13
> >> 20 23
> >>
> >> I would appreciate it if someone could write me how to do it.
> >
> >
> > For you data in a data.frame called dat:
> >
> > aggregate(measured ~ par, dat, mean)
> >
> > Uwe Ligges
> >
> >
> >>
> >> Thank you,
> >> Irek
> >>
> >> ______________________________________________
> >> 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.
> >
>
>
> --
> Ireneusz (Irek) Szczesniak
> http://www.irkos.org
>
> ______________________________________________
> 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.
______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
