# [R] Variance

Andrew Robinson A.Robinson at ms.unimelb.edu.au
Fri Apr 29 00:24:01 CEST 2011

```A couple of points here ....

First, note that q doesn't increment in the code below.  So, you're
getting the same variance each time.

Second, note that (t\$Rec1==input3 & t\$Rec2==input4) evaluates to F?T
or 0/1, and it's not clear from your code if that is what you intend.

Finally, it's much easier to work with commented, minimal,
self-contained, reproducible code.  Please consider submitting that
with future questions.

I hope that this helps,

Andrew.

On Thu, Apr 28, 2011 at 05:58:24PM -0400, Dat Mai wrote:
> I'm trying to find the variance of various outputs in a matrix:
>
> for(l in 2:vl){
>   for(o in 1:(l-1)){
>
>     # Make sure the inputs are for the matrix "m"
>     input3=rownames(v)[o]
>     input4=colnames(v)[l]
>
>     r=t[(t\$Rec1==input3 & t\$Rec2==input4),output]
>
>     if(length(r)==0){
>       r=t[(t\$Rec1==input4 & t\$Rec2==input3),output]
>     }
>
>     v[l,o]=var(q,na.rm=TRUE)
>     v[o,l]=var(q,na.rm=TRUE)
>     v[l,l]=var(q,na.rm=TRUE)
>
>   }
> }
>
> Each output will yield multiple results, since each input length varies.
> I'm not sure if this is the right way to go about finding the variance of
> each pair, but this is what I've done.
> The main issue I have with this now is that the results in every box in the
> matrix yield the same exact number, even though that most likely shouldn't
> happen.
>
> The question is: "How would I find the variance of each pair of inputs?"
>
> 	[[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> and provide commented, minimal, self-contained, reproducible code.

--
Andrew Robinson
Program Manager, ACERA
Department of Mathematics and Statistics            Tel: +61-3-8344-6410
University of Melbourne, VIC 3010 Australia               (prefer email)
http://www.ms.unimelb.edu.au/~andrewpr              Fax: +61-3-8344-4599
http://www.acera.unimelb.edu.au/

Forest Analytics with R (Springer, 2011)
http://www.ms.unimelb.edu.au/FAwR/
Introduction to Scientific Programming and Simulation using R (CRC, 2009):
http://www.ms.unimelb.edu.au/spuRs/

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