Hi David,

this sounds like a rather complicated problem to me. But perhaps I do not
understand your real problem at hand.
Could you try to be a little more specific, i.e. give a little background as
where this problem comes from?

As I read it, you have data, that are corrupted by noise that is dependent
on the magnitude of the data itself.
I think it would be possible to come out with a model in principle. Do you
know anything about how the noise depends on the data? Do you know anything
about the noise?

I personally would not try simply throwing away, some of the data completely
(also this would destroy the original distribution), but use them (in a
weighted way) because they still contain valuable information.

regards,
Roland


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