[R] implementing Grubbs outlier test on a large dataframe

[David Winsemius]

Sending each row of a datatframe, dfm,  as a vector to a function,  
fcn, is as simple as;

apply(dfm, 1, fcn)

e.g.:

 > dfm <- data.frame(x=rnorm(10), y=rnorm(10), z=rnorm(10))
 >
 > apply(dfm, 1, sum)
  [1]  0.7385838 -3.1819193  0.3415670 -0.6552601 -1.3470174  
-0.6446259 -0.6544967
  [8]  0.1778169 -0.3330527  0.6246071

And with the second argument set to 2, you would get a columnwise  
application of the function.

You need to show us what your function looks like to go any further. I  
am unclear how one could get a function that only operates on a single  
row to yield an outlier classification.

-- 
David Winsemius
On Feb 14, 2009, at 6:01 PM, John Malone wrote:

> Hi!
>
> I'm trying to implement an outlier test once/row in a large dataframe.
> Ideally, I'd do this then add the Pvalue results and the number  
> flagged as
> an outlier as two new separate columns to the dataframe.  Grubbs  
> outlier
> test requires a vector and I'm confused how to make each row of my  
> dataframe
> a vector, followed by doing a Grubbs test for each row containing  
> the vector
> of numbers I want to perform the outlier test on.
>
> I'm new to R and no doubt this is a simple problem. Any help you might
> provide would be greatly appreciated.
>
> Many thanks in advance!!
>
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>
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