diff --git a/R/ZIPLNfit-S3methods.R b/R/ZIPLNfit-S3methods.R
index df9e916d..a158c241 100644
--- a/R/ZIPLNfit-S3methods.R
+++ b/R/ZIPLNfit-S3methods.R
@@ -122,10 +122,9 @@ isZIPLNfit_sparse <- function(Robject) {inherits(Robject, "ZIPLNfit_sparse")}
 #' @examples
 #' data(trichoptera)
 #' trichoptera <- prepare_data(trichoptera$Abundance, trichoptera$Covariate)
-#' fits <- ZIPLN(Abundance ~ 1, data = trichoptera, control = ZIPLN_param(penalty = 0.1))
-#' myNet <- getBestModel(fits)
+#' fit <- ZIPLN(Abundance ~ 1, data = trichoptera, control = ZIPLN_param(penalty = 0.1))
 #' \dontrun{
-#' plot(myNet)
+#' plot(fit)
 #' }
 #' @export
 plot.ZIPLNfit_sparse <-
diff --git a/R/ZIPLNfit-class.R b/R/ZIPLNfit-class.R
index 8b63ec50..2151f9d3 100644
--- a/R/ZIPLNfit-class.R
+++ b/R/ZIPLNfit-class.R
@@ -730,9 +730,10 @@ ZIPLNfit_fixed <- R6Class(
 #' # See other examples in function ZIPLN
 #' data(trichoptera)
 #' trichoptera <- prepare_data(trichoptera$Abundance, trichoptera$Covariate)
-#' myPLN <- ZIPLN(Abundance ~ 1, data = trichoptera, control=  ZIPLN_param(penalty = 0.2))
+#' myPLN <- ZIPLN(Abundance ~ 1, data = trichoptera, control=  ZIPLN_param(penalty = 1))
 #' class(myPLN)
 #' print(myPLN)
+#' plot(myPLN)
 #' }
 ZIPLNfit_sparse <- R6Class(
   classname = "ZIPLNfit_sparse",