[R] Questions on Mahalanobis Distance

[Sarah Goslee]

If the goal is to *use* the Mahalanobis distance, rather than to learn
how to write your own code, there are several existing implementations.
rseek.org is a good place to find functions.

Sarah

On Fri, Jan 29, 2010 at 9:48 PM, Robert Lonsinger
<rob.lonsinger at gmail.com> wrote:
> Hello,
> I am a new R user and trying to learn how to implement the mahalanobis
> function to measure the distance between to 2 population centroids.  I
> have used STATISTICA to calculate these differences, but was hoping to learn
> to do the analysis in R.  I have implemented the code as below, but my
> results are very different from that of STATISTICA, and I believe I may not
> have interpreted the help correctly and may have implemented the
> code incorrectly.
>
> Though I am not certain, I believe that my error may be in calculating the
> common covariance matrix (the third argument supplied to the mahalanobis
> funtion).
>
> Any help or guidance would be greatly appreciated.
>
> Thank you! RL
>
> CODE
>
> fit<-lda(pop~v1 + v2 + v3 +...+vn, data=my.data)
>
> x1<-subset(my.data, pop==1)
>
> x2<-subset(my.data, pop==2)
>
>
>
>  #Save Covariance Matices for each group
> cov1<-cov(x1)
> cov2<-cov(x2)
>
>
>
> #Determine number of rows in each matrix
> n1<-nrow(x1); n2<-nrow(x2);
> n.rows<-c(n1,n2)
>
>
> #store mean vectors from lda object
> mu1<-fit$means[1,]
> mu2<-fit$means[2,]
>
>
>
> #Calculate the common Covariance Matrix
> S<-(((n.rows[1]-1)*cov1)+((n.rows[2]-1)*cov2)/ (sum(n.rows[1:2])-1))
>
> #Calculate the common Covariance Matrix
> mahalanobis(mu1, mu2, S)
>
>        [[alternative HTML version deleted]]
>
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>



-- 
Sarah Goslee
http://www.functionaldiversity.org