covariance matrix in R

covmatrix.r

define x and y

x<-c(2.5,.5,2.2,1.9,3.1,2.3,2,1,1.5,1.1)
y<-c(2.4,.7,2.9,2.2,3.0,2.7,1.6,1.1,1.6,.9)

create a covariance matrix the hard way

cm<-matrix(data=c(cov(x,x),cov(x,y),cov(y,x),cov(y,y)),nrow=2,ncol=2)
> cm
          [,1]      [,2]
[1,] 0.6165556 0.6154444
[2,] 0.6154444 0.7165556
> 

edit: thanks to @johnmyleswhite (as usual), here is the solution:

http://twitter.com/johnmyleswhite/status/24749000734
@neilkod In general, lots of the single vector functions work on data frames in a sensible way.

http://twitter.com/johnmyleswhite/status/24748937928
@neilkod cov(data.frame(x, y))

> cov(data.frame(x,y))
          x         y
x 0.6165556 0.6154444
y 0.6154444 0.7165556
> data.frame(x,y)
     x   y
1  2.5 2.4
2  0.5 0.7
3  2.2 2.9
4  1.9 2.2
5  3.1 3.0
6  2.3 2.7
7  2.0 1.6
8  1.0 1.1
9  1.5 1.6
10 1.1 0.9
> 

This is a case where you probably actually should use cbind: cov(cbind(x, y))