Thank you, William, for your help! It works great. My final call
looks like this:
pars <- c(.(nodes), .(load), .(buffer), .(deflections))
ddply(i, pars, summarize,
mm_created = mean(mean_created),
ms_created = mean(sdev_created),
mm_admitted = mean(mean_admitted),
ms_admitted = mean(sdev_admitted),
mm_dropped = mean(mean_dropped),
ms_dropped = mean(sdev_dropped),
mm_delivered = mean(mean_delivered),
ms_delivered = mean(sdev_delivered))
2012/1/18 William Dunlap <wdun...@tibco.com>:
> 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.
______________________________________________
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.
