Dear Colin,
Try this:

# Data
DF <- structure(c(0, 0, 0, 4, 27, 0, 1, 0, 7, 16, 1, 0, 0, 16, 44,
0, 0, 0, 2, 39), .Dim = c(5L, 4L), .Dimnames = list(c("L01.1",
"L01.2", "L01.3", "L01.4", "L01.5"), c("P01", "P02", "P03", "P04"
)))

# Distances
Names<-t(combn(colnames(DF),2))
apply(Names,1,function(x) JostD(x[1],x[2], DF))

HTH,

Jorge



On Fri, Mar 27, 2009 at 1:33 PM, Colin Garroway <colin.garroway@gmail.com>wrote:

> Hello,
>
> I have written a small function ('JostD' based upon a recent molecular
> ecology paper) to calculate genetic distance between populations (columns
> in
> my data set).  As I have it now I have to tell it which 2 columns to use
> (X,
> Y).  I would like it to automatically calculate 'JostD' for all
> combinations
> of columns, perhaps returning a matrix of distances.  Thanks for any help
> or
> suggestions.
> Cheers
> Colin
>
>
>
> Function:
>
> JostD <- function(DF, X, Y) {
>
>    Ni1 <- DF[,X]
>    Ni2 <- DF[,Y]
>
>    N1 <- sum(Ni1)
>    N2 <- sum(Ni2)
>
>    pi1 <-Ni1/N1
>    pi2 <-Ni2/N2
>        pisqr <- ((pi1+pi2)/2)^2
>
>    H1 <- 1 - sum(pi1^2)
>    H2 <- 1 - sum(pi2^2)
>    Ha <- 0.5*(H1+H2)
>
>    Da <- 1/(1-Ha)
>        Dg <- 1/sum(pisqr)
>        Db <- Dg/Da
>        D <- -2*((1/Db) - 1)
>    D
> }
>
> Sample data:
>
> e<-c(0,0,0,4,27)
> r<-c(0,1,0,7,16)
> t<-c(1,0,0,16,44)
> y<-c(0,0,0,2,39)
> df<-cbind(e,r,t,y)
> rownames(df)<-q
> colnames(df)<-w
>
> > df
>      P01 P02 P03 P04
> L01.1   0   0   1   0
> L01.2   0   1   0   0
> L01.3   0   0   0   0
> L01.4   4   7  16   2
> L01.5  27  16  44  39
>
> > JostD(df, 1, 2)
> [1] 0.0535215
>
> > JostD(df, 1, 3)
> [1] 0.02962404
> >
>
>
>
>
>
> --
> Colin Garroway (PhD candidate)
> Wildlife Research and Development Section
> Ontario Ministry of Natural Resources
> Trent University, DNA Building
> 2140 East Bank Drive
> Peterborough, ON, K9J 7B8
> Canada
>
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>
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

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