weighted quantile bug fix#134
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iii-org-tw wants to merge 13 commits intoharrelfe:masterfrom
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patching the lowest index 1
change linear
Update the function according to https://stats.stackexchange.com/questions/13169/defining-quantiles-over-a-weighted-sample formula
Update naming
change linear Update wtd.stats.s Update the function according to https://stats.stackexchange.com/questions/13169/defining-quantiles-over-a-weighted-sample formula Update wtd.stats.s Update naming
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Hi @harrelfe Do you have time to review this PR? |
Owner
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Would you mind doing some tests on how this changes behavior in the non-breaking case? Also I would need changes in the help file to go along with these changes. Thanks for working on this. |
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Original code has two problems:
This line goes wrong. The indexing becomes descending.
For example:
It is because the cumsum is 0.3, 0.6, 3.0 and the approx function try to locate lower index 1 and upper index 2.
It turns both q take the 3 value and the interpolation crush.
I find one formula to define weighted quantile.
https://stats.stackexchange.com/questions/13169/defining-quantiles-over-a-weighted-sample
It is well defined in boundary and the result equals to numpy quantile when weights are equal.
I implement the code accordingly and this one doesn't have the above mentioned problem.
Any review is welcome.