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I'm looking for some easy to use algorithms in R to label (outlier or not) or score (say, 7.5) outliers row-wise. Meaning, I have a matrix m that contains several rows and I want to identify rows who represent outliers compared to the other rows.

m <- matrix( data = c(1,1,1,0,0,0,1,0,1), ncol = 3 )

To illustrate some more, I want to compare all the (complete) rows in the matrix with each other to spot outliers.

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Here's some really simple outlier detection (using either the boxplot statistics or quantiles of the data) that I wrote a few years ago.

Outliers

But, as noted, it would be helpful if you'd describe your problem with greater precision.

Edit:

Also you say you want row-wise outliers. Do you mean to say that you're interested in identifying whole rows vs observations within a variable (as is typically done)? If so, you'll want to use some sort of distance metric, though which metric you choose will depend on your data.


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