I have a dataset that follows something between a power and exponential law. I'm not happy with the IQR method of detection of outliers because on small sets of data (<50-100), it does not give you an idea of the percentage of outliers that have been droped.

I thought of an iterative method that would drop on each iteration the most outlying number until the the desired percentage is reached. I could run this method only when the IQR method drops more than the desired percentage.

Does it make sense and is there a standard way of dealing with this problem ?

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