1 files changed, 6 insertions, 5 deletions
diff --git a/R/logLik.mkinfit.R b/R/logLik.mkinfit.R
index cadc0d0a..1c025893 100644
--- a/R/logLik.mkinfit.R
+++ b/R/logLik.mkinfit.R
@@ -1,15 +1,15 @@
 #' Calculated the log-likelihood of a fitted mkinfit object
-#' 
+#'
 #' This function returns the product of the likelihood densities of each
 #' observed value, as calculated as part of the fitting procedure using
 #' \code{\link{dnorm}}, i.e. assuming normal distribution, and with the means
 #' predicted by the degradation model, and the standard deviations predicted by
 #' the error model.
-#' 
+#'
 #' The total number of estimated parameters returned with the value of the
 #' likelihood is calculated as the sum of fitted degradation model parameters
 #' and the fitted error model parameters.
-#' 
+#'
 #' @param object An object of class \code{\link{mkinfit}}.
 #' @param \dots For compatibility with the generic method
 #' @return An object of class \code{\link{logLik}} with the number of estimated
@@ -19,7 +19,7 @@
 #' @seealso Compare the AIC of columns of \code{\link{mmkin}} objects using
 #'   \code{\link{AIC.mmkin}}.
 #' @examples
-#' 
+#'
 #'   \dontrun{
 #'   sfo_sfo <- mkinmod(
 #'     parent = mkinsub("SFO", to = "m1"),
@@ -31,11 +31,12 @@
 #'   f_tc <- mkinfit(sfo_sfo, d_t, error_model = "tc", quiet = TRUE)
 #'   AIC(f_nw, f_obs, f_tc)
 #'   }
-#' 
+#'
 #' @export
 logLik.mkinfit <- function(object, ...) {
   val <- object$logLik
   # Number of estimated parameters
   attr(val, "df") <- length(object$bparms.optim) + length(object$errparms)
+  class(val) <- "logLik"
   return(val)
 }