On Mon, 8 Aug 2005, alessandro carletti wrote:
> Hi everybody,
> I'd like to know if there's an easy way for extracting
> outliers record from a dataset, in order to perform
> further analysis on them.
The answer is "no". The reasons are not technical. There are some quite
easy outlier detection approaches around (e.g., compute robust Mahalanobis
distances with cov.mcd/mahalanobis and call the points with too large
But the main problem is that the term outlier has no objective, unique meaning. It depends crucially on your aims and on the assumptions you want to make about the non-outliers in the dataset (which should be elliptically distributed and homogeneously close to a multivariate normal distribution for the Mahalanobis approach).
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