#' Build a generic model
#'
#' Check conformity of arguments and return a \code{generic} object.
#'
#' A generic random effect stores the incidence and structure matrices in Matrix
#' form, which tries to take advantage of sparsity, if it exists.
#'
#' @inheritParams random
#' @return A list with elements \code{incidence.matrix}, \code{structure.matrix}
#' and \code{structure.type}, which is a string indicating either
#' \code{covariance} or \code{precision}.
generic <- function(incidence, covariance, precision) {
## Try converting to Matrix class (either sparse or dense)
mc <- match.call()
## Build the random effect, and further specify the generic class
random.call <- mc
random.call[[1]] <- as.symbol('random')
ans <- eval(random.call, parent.frame())
class(ans) <- c('generic', class(ans))
return(ans)
}
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