[R] Identification of Outliners and Extraction of Samples

[Frank Harrell]

On Mon, 9 Aug 2010, Alexander Eggel wrote:

> Hello everybody,
>
> I need to know which samples (S1-S6) contain a value that is bigger than the
> median + five standard deviations of the column he is in. This is just an

Why not the 70th percentile plus 6 times the difference in the 85th 
and 75th percentiles  :-)

Frank

P.S.  See

@Article{fin06cal,
   author = 		 {Finney, David J.},
   title = 		 {Calibration guidelines challenge outlier 
practices},
   journal = 	 The American Statistician,
   year = 		 2006,
   volume =		 60,
   pages =		 {309-313},
   annote =		 {anticoagulant
therapy;bias;causation;ethics;objectivity;outliers;guidelines for
treatment of outliers;overview of types of outliers;letter to the 
editor and reply 61:187 May 2007}
}


> example. Command should be applied to a data frame wich is a lot bigger
> (over 100 columns). Any solutions? Thank you very much for your help!!!
>
>> s
>    Samples     A     B    C    E
> 1             S1   1     2     3     7
> 2             S2   4    NA   6     6
> 3             S3   7     8     9    NA
> 4             S4   4     5    NA   6
> 5             S5   2     5     6     7
> 6             S6   2     3     4     5
>
> This loop works fine for a column without NA values. However it doesn't work
> for the other columns. I should have a loop that I could apply to all
> columns ideally in "one command".
>
> o <- data.frame();
> for (i in 1:nrow(s))
> {
>       dd <- s[i,];
>       if (dd$A >= median(s$A, na.rm=TRUE) + 5 * sd(s$A, na.rm=TRUE)) o <-
> rbind(o,dd)
>
> }
>
> 	[[alternative HTML version deleted]]
>
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