#' ICOMP
#'
#' Generic function for calculating Bozdogan's information complexity
#' measure (ICOMP). ICOMP is a likelihood-based criterion similar
#' to Akaike's Information Criterion (AIC). As with AIC,
#' a smaller ICOMP value corresponds to a better model.
#'
#' @param object
#' A model for which there is a method for \code{stats::logLik()}.
#' Currently supports \code{lm} objects.
#' @param ...
#' Additional arguments.
#'
#' @return
#' The ICOMP value for the given model.
#'
#' @author Drew Schmidt and Jake Ferguson
#'
#' @references Bozdogan, H. Haughton, D.M.A (1998). Information complexity
#' criteria for regression models. Computation Statistics & Data Analysis 28:
#' 51-76
#'
#' @keywords models regression
#' @rdname ICOMP
#' @export
ICOMP <- function(object, ...) UseMethod("ICOMP")
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