From: Andrew Clausen <clausen_at_econ.upenn.edu>

Date: Mon, 14 May 2007 00:32:55 -0400

R-devel_at_r-project.org mailing list

https://stat.ethz.ch/mailman/listinfo/r-devel Received on Mon 14 May 2007 - 04:35:10 GMT

Date: Mon, 14 May 2007 00:32:55 -0400

Thanks for the interesting suggestion. I must confess I got lost -- is it something like this?

relist <- function(flesh, skeleton=attributes(flesh)$skeleton)

For example:

par <- list(mean=c(0, 0), vcov(rbind(c(1, 1), c(1, 1)))) vector.for.optim <- unlist(par) print(attributes(vector.optim)$skeleton) # the skeleton is stored! converted.back.again <- relist(par)

Some concerns:

- the metadata might get lost in some applications -- although it seems to work fine with optim(). But, if we provide both interfaces (where skeleton=flesh$skeleton is the default), then there should be no problem.
- would there be any bad side-effects of changing the existing unlist interface? I suppose an option like "save.skeleton" could be added to unlist. I expect there would be some objections to enabling this as default behaviour, as it would significantly increase the storage requirements of the output.

Cheers,

Andrew

On Sun, May 13, 2007 at 07:02:37PM -0400, Gabor Grothendieck wrote:

> I suggest you define a "relist" class and then define an unlist

*> method for it which stores the skeleton as an attribute. Then
**> one would not have to specify skeleton in the relist command
**> so
**>
**> relist(unlist(relist(x))) === x
**>
**> 1. relist(x) is the same as x except it gets an additional class "relist".
**> 2. unlist(relist(x)) invokes the relist method of unlist on relist(x)
**> returning another relist object
**> 3. relist(unlist(relist(x))) then recreates relist(x)
**>
**>
**> On 5/13/07, Andrew Clausen <clausen_at_econ.upenn.edu> wrote:
**> >Hi all,
**> >
**> >I wrote a function called relist, which is an inverse to the existing
**> >unlist function:
**> >
**> > http://www.econ.upenn.edu/~clausen/computing/relist.R
**> >
**> >Some functions need many parameters, which are most easily represented in
**> >complex structures. Unfortunately, many mathematical functions in R,
**> >including optim, nlm, and grad can only operate on functions whose domain
**> >is
**> >a vector. R has a function to convert complex objects into a vector
**> >representation. This file provides an inverse operation called "unlist" to
**> >convert vectors back to the convenient structural representation.
**> >Together,
**> >these functions allow structured functions to have simple mathematical
**> >interfaces.
**> >
**> >For example, a likelihood function for a multivariate normal model needs a
**> >variance-covariance matrix and a mean vector. It would be most convenient
**> >to
**> >represent it as a list containing a vector and a matrix. A typical
**> >parameter
**> >might look like
**> >
**> > list(mean=c(0, 1), vcov=cbind(c(1, 1), c(1, 0)))
**> >
**> >However, optim can't operate on functions that take lists as input; it
**> >only likes vectors. The solution is conversion:
**> >
**> > initial.param <- list(mean=c(0, 1), vcov=cbind(c(1, 1), c(1, 0)))
**> >
**> > ll <- function(param.vector)
**> > {
**> > param <- relist(initial.param, param.vector)
**> > -sum(dnorm(x, mean=param$mean, vcov=param$vcov, log=TRUE))
**> > # note: dnorm doesn't do vcov... but I hope you get the
**> > point
**> > }
**> >
**> > optim(unlist(initial.param), ll)
**> >
**> >"relist" takes two parameters: skeleton and flesh. Skeleton is a sample
**> >object that has the right "shape" but the wrong content. "flesh" is a
**> >vector
**> >with the right content but the wrong shape. Invoking
**> >
**> > relist(skeleton, flesh)
**> >
**> >will put the content of flesh on the skeleton.
**> >
**> >As long as "skeleton" has the right shape, it should be a precise inverse
**> >of unlist. These equalities hold:
**> >
**> > relist(skeleton, unlist(x)) == x
**> > unlist(relist(skeleton, y)) == y
**> >
**> >Is there any easy way to do this without my new relist function? Is there
**> >any
**> >interest in including this in R's base package? (Or anywhere else?) Any
**> >comments on the implementation?
**> >
**> >Cheers,
**> >Andrew
**> >
**> >______________________________________________
**> >R-devel_at_r-project.org mailing list
**> >https://stat.ethz.ch/mailman/listinfo/r-devel
**> >
*

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