Is there any solution to fit plane onto sampling data?
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For example I have the variables x, y (or higher dimensional data in general) and a probability distribution p(x,y). I want to approximate p(x,y) as a linear function, a plane in this case, at least somewhere in the domain. However I only have samples from the distribution. In case of big amount of data the easy way is to collect them into bins, and fit a plane onto the estimated density function. But I dont want to compress data, I would like to extract the maximum information and use the points itself. Are there any method to do this?
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Peter Borda
2015-1-9
0 个投票
I'm not sure if I understand the problem correctly, but if you have a high number of sample point on which you have to fit a plane of any dimensions, you can use this method:
2 个评论
Mr M.
2015-1-9
Nikola Stan
2021-9-1
having (x,y,p(x,y)) is equivalent to having (x,y,z) triplets
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