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I know that there are variants of the arithmetic mean and the median that are applicable to three dimensional data (centroid and medoid), but have not been able to find such a thing for the modal average.

Now I know that modal averaging could just as well be applied to 3d data (it would just yield the coordinate that occurs most frequently), but the data i'm averaging probably won't have any values that occur more than once.

So what i'm looking for would not require the datapoints to be exactly alike, but alike to a certain degree (say X% similarity), as a tradeoff (if a numerical majority cannot be found). Is there such a thing? Or would this yield exactly the same result as the medoid?

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I suspect the most practical approach would be multidimensional kernel density estimation, and then choose the point with highest kernel density. This will depend on your assumptions, particularly over bandwidth.

The np package in R may help.

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    Excellent, i'll get to it then, thanks for the answer!2012-02-29