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#' Print method for PRC-MLPMM model fits
#'
#' @param x an object of class \code{prcmlpmm}
#' @param digits number of digits at which the printed estimated regression
#' coefficients should be rounded (default is 4)
#' @param ... additional arguments
#'
#' @return Summary information about the fitted PRC-MLPMM model
#'
#' @export
#' @author Mirko Signorelli
#' @references
#' Signorelli, M. (2024). pencal: an R Package for the Dynamic
#' Prediction of Survival with Many Longitudinal Predictors.
#' To appear in: The R Journal. Preprint: arXiv:2309.15600
#'
#' Signorelli, M., Spitali, P., Al-Khalili Szigyarto, C,
#' The MARK-MD Consortium, Tsonaka, R. (2021).
#' Penalized regression calibration: a method for the prediction
#' of survival outcomes using complex longitudinal and
#' high-dimensional data. Statistics in Medicine, 40 (27), 6178-6196.
#' DOI: 10.1002/sim.9178
#'
#' @seealso \code{\link{fit_prcmlpmm}}, \code{\link{summary.prcmlpmm}}
print.prcmlpmm = function(x, digits = 4, ...) {
print.prclmm(x, digits)
}
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