R help - Feb 2012 - entropy package: how to compute mutual information?

suppose I have two factor vectors:
 x <-
as.factor(c("a","b","a","c","b","c"))
 y <-
as.factor(c("b","a","a","c","c","b"))
I can compute their entropies:
 entropy(table(x))
[1] 1.098612
using
 library(entropy)
but it is not clear how to compute their mutual information directly.
I can compute the joint entropy as
  entropy(table(paste(x,y,sep="")))
[1] 1.791759
and then mutual information will be h(x) + h(y) - h(x,y) 1.098612 + 1.098612 -
1.791759
0.405465

but I was wondering whether there was a better way (without creating a
fresh factor vector and a fresh factor class, both of which are
immediately discarded).


-- 
Sam Steingold (http://sds.podval.org/) on Ubuntu 11.10 (oneiric) X 11.0.11004000
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> * Sam Steingold <fqf at tah.bet> [2012-02-13 16:14:36 -0500]:
>
> suppose I have two factor vectors:
>  x <-
as.factor(c("a","b","a","c","b","c"))
>  y <-
as.factor(c("b","a","a","c","c","b"))
> I can compute their entropies:
>  entropy(table(x))
> [1] 1.098612
> using
>  library(entropy)
> but it is not clear how to compute their mutual information directly.
> I can compute the joint entropy as
>   entropy(table(paste(x,y,sep="")))
this can be simplified to entropy(table(x,y))
> [1] 1.791759
> and then mutual information will be h(x) + h(y) - h(x,y) > 1.098612 +
1.098612 - 1.791759
> 0.405465
>
> but I was wondering whether there was a better way (without creating a
> fresh factor vector and a fresh factor class, both of which are
> immediately discarded).
-- 
Sam Steingold (http://sds.podval.org/) on Ubuntu 11.10 (oneiric) X 11.0.11004000
http://www.childpsy.net/ http://ffii.org http://mideasttruth.com
http://thereligionofpeace.com http://americancensorship.org http://memri.org
If money were measured in piles, I would have had a pit of it.