documentation added

man/stats_outlier.Rd

@@ -4,14 +4,16 @@
 \alias{stats_outlier}
 \title{Outlier detection}
 \usage{
-stats_outlier(dt, check_col = "ppm", ...)
+stats_outlier(dt, check_col = "ppm", msg = FALSE, ...)
 }
 \arguments{
 \item{dt}{data.table or data.frame}
 
 \item{check_col}{Name of column (quoted string) for which outlier detection should be performed}
 
-\item{...}{zero or more objects which can be coerced to character (and which are pasted together with no separator) or a single condition object.}
+\item{msg}{return messages}
+
+\item{...}{zero or more objects that can be coerced to character (and which are pasted together with no separator) or a single condition object.}
 }
 \value{
 Plot
@@ -21,9 +23,5 @@ This function will return a score for potential outlier values (out_score).
 It is based on four consecutive outlier tests, each of which will increase "out_score" by 1 if an outlier was detected.
 The four tests are based on interquartile range (IQR), 2.5 / 97.5 quantile cut-off, Hampel test, Rosner test
 If all four tests are True for a value, "out_score" has a value of "4"
-}
-\examples{
-stats_outlier(dt = ume::mf_data_demo, check_col = "ppm")
-
 }
 \keyword{misc}