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I have following data given:

enter image description here

My curve fits it acceptable for my needs. I use here 4th degree polynomial. (data is limited to 0-100 percent range for both axis!)

What I want to try now is to filter those outliers you can see in the picture. In following I mark outlier-regions red (as I think of):

enter image description here

I have no problems removing outliers from 1D data based on mean or median approach but how to do this with 2D data?

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First, contrary to the comment, I do think your data are two dimensional - you have two variables. The 4th degree polynomial will have a Y variable and an X variable (presumably load in % is the Y variable).

Second, detecting outliers is a very tricky problem. In two dimensional data, one method would be kernel densities. See this thread, for example.

Finally, questions about how to do things in a particular software packageare off topic here.

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    $\begingroup$ I think my comment was misinterpreted. I say that the OP "clearly treated them as 1D"; I am not commenting on whether they are not or not. Probably I should have said "... as how are these 2D in your current problem formulation;". Whether there is a quartic relation is debatable but the OP appears OK with that ("My curve fits it acceptable for my needs.") Clearly in most data analysis scenario there exists a continuum over which the data are registered (eg. height-age, metabolic rate-temperature, etc.). $\endgroup$ – usεr11852 Jan 22 '16 at 20:47
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    $\begingroup$ This reads like a series of comments. What new answer are you offering, exactly? $\endgroup$ – whuber Jan 22 '16 at 21:38

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