utils (version 3.6.2)

relist: Allow Re-Listing an unlist()ed Object


relist() is an S3 generic function with a few methods in order to allow easy inversion of unlist(obj) when that is used with an object obj of (S3) class "relistable".


relist(flesh, skeleton)
# S3 method for default
relist(flesh, skeleton = attr(flesh, "skeleton"))
# S3 method for factor
relist(flesh, skeleton = attr(flesh, "skeleton"))
# S3 method for list
relist(flesh, skeleton = attr(flesh, "skeleton"))
# S3 method for matrix
relist(flesh, skeleton = attr(flesh, "skeleton"))

as.relistable(x) is.relistable(x)

# S3 method for relistable unlist(x, recursive = TRUE, use.names = TRUE)



a vector to be relisted


a list, the structure of which determines the structure of the result


an R object, typically a list (or vector).


logical. Should unlisting be applied to list components of x?


logical. Should names be preserved?


an object of (S3) class "relistable" (and "list").


Some functions need many parameters, which are most easily represented in complex structures, e.g., nested lists. Unfortunately, many mathematical functions in R, including optim and nlm can only operate on functions whose domain is a vector. R has unlist() to convert nested list objects into a vector representation. relist(), its methods and the functionality mentioned here provide the inverse operation to convert vectors back to the convenient structural representation. This allows structured functions (such as optim()) 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 cannot operate on functions that take lists as input; it only likes numeric vectors. The solution is conversion. Given a function mvdnorm(x, mean, vcov, log = FALSE) which computes the required probability density, then

        ipar <- list(mean = c(0, 1), vcov = c bind(c(1, 1), c(1, 0)))
        initial.param <- as.relistable(ipar)

ll <- function(param.vector) { param <- relist(param.vector, skeleton = ipar) -sum(mvdnorm(x, mean = param$mean, vcov = param$vcov, log = TRUE)) }

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(flesh, skeleton)

will put the content of flesh on the skeleton. You don't need to specify skeleton explicitly if the skeleton is stored as an attribute inside flesh. In particular, if flesh was created from some object obj with unlist(as.relistable(obj)) then the skeleton attribute is automatically set. (Note that this does not apply to the example here, as optim is creating a new vector to pass to ll and not its par argument.)

As long as skeleton has the right shape, it should be a precise inverse of unlist. These equalities hold:

   relist(unlist(x), x) == x
   unlist(relist(y, skeleton)) == y

x <- as.relistable(x) relist(unlist(x)) == x

See Also



Run this code
 ipar <- list(mean = c(0, 1), vcov = cbind(c(1, 1), c(1, 0)))
 initial.param <- as.relistable(ipar)
 ul <- unlist(initial.param)
 stopifnot(identical(relist(ul), initial.param))
# }

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