coerce a multiple output in a new dataframe using ddply

Question

I have this function:

> λ.est <- function(x){
            mle.optim <- mle2(paretoNLL,start=list(λ=-0.7),data=list(x=x),trace=TRUE)
            return(summary(mle.optim)@coef[1,1:4])
            }

that fit a distribution and retuns the parameter estimate, std. error, z value and p for my model. I have to apply this function to different subsets of my original data frame size defined by a combination of factor pond,habitat,treatment,date , and to do this I'm using the ddply function:

> mle.λ <- ddply(size, .(pond,habitat,treatment,date), 
     summarise, λ=λ.est(x=mass.wei))

the problem is that, by doing this, I can only add one column a time to the new data frame mle.λ , wereas I need to add to mle.λ four new columns, one for each of the outputs of λ.est basically something that look like this:

>  mle.λ
      pond habitat treatment date estimate std. error z value Pr(z)
       -    -        -       -      -        -         -      - 
       -    -        -       -      -        -         -      - 
       -    -        -       -      -        -         -      - 
       -    -        -       -      -        -         -      - 
       -    -        -       -      -        -         -      - 
      ...

So far I've been writing a different function for each output needed, but I'd like to do some code economy...is there any way to do it all in one go?

thanks matteo

Answer 1

Since you already have a summary function, you don't need to additionally use the summarise function. Further, it is possible to return more than one output at once. Since there is no example data, here is one that should demonstrate clearly how to do this:

n = 20
set.seed(12345)
data = data.frame(cbind(pond=1:2, habitat=1:3, value = rnorm(n)))

> ddply(data, .(habitat, pond), function(x) summary(x$value))
  habitat pond    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.
1       1    1  0.3706  0.5318  0.6078  0.6767  0.7528  1.1210
2       1    2 -0.9193 -0.6864 -0.4535 -0.1853  0.1817  0.8169
3       2    1 -0.8864 -0.5013 -0.1162 -0.1322  0.2448  0.6059
4       2    2 -0.2762  0.1550  0.4095  0.3131  0.5675  0.7095
5       3    1 -0.7505 -0.5173 -0.2842 -0.3813 -0.1967 -0.1093
6       3    2 -1.8180 -1.0750 -0.3316 -0.1107  0.7429  1.8170