Advanced, but easy to use outlier rejection.
Project description
A suite of algorithms for powerful, but easy to use statistical outlier detection/rejection. Especially useful for cleaning heavily (sometimes >85%) contaminated datasets, while avoiding the rejection of non-outlier points. Supports weighted datasets, multi-dimensional model fitting, and much more. See https://github.com/nickk124/RCR for more information.
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