# [Rd] relist, an inverse operator to unlist

Andrew Clausen clausen at econ.upenn.edu
Sun May 13 19:29:11 CEST 2007

```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

```