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EmpiricalCDFs.jl

Empirical cumulative distribution functions

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Provides empirical cumulative distribution functions (CDFs) (or "empirical distribution functions" as they are know to probabalists).

See the documentation https://jlapeyre.github.io/EmpiricalCDFs.jl/latest.

I'm surprised that this module is not more popular (if stars are a good measure) because it's rather generic, I use it frequently for new projects, and the functionality is not available elsewhere. In the meantime it's gained some stars.

EmpiricalCDFs implements empirical CDFs; building, evaluating, random sampling, evaluating the inverse, etc. It is useful especially for examining the tail of the CDF obtained from streaming a large number of data, more than can be stored in memory. For this purpose, you specify a lower cutoff; data points below this value will be silently rejected, but the resulting CDF will still be properly normalized. This ability to process and filter data online is absent in StatsBase.ecdf.