A new data structure for accurate on-line accumulation of rank-based statistics such as quantiles and trimmed means
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Updated
Dec 19, 2023 - Java
A new data structure for accurate on-line accumulation of rank-based statistics such as quantiles and trimmed means
A C++ header-only library of statistical distribution functions.
t-Digest data structure in Python. Useful for percentiles and quantiles, including distributed enviroments like PySpark
Boosted trees in Julia
weighted quantiles with Python
t-digest module for Redis
Robust Graphical Methods For Group Comparisons
DynaHist: A Dynamic Histogram Library for Java
Efficient Sequential and Batch Estimation of Univariate and Bivariate Probability Density Functions and Cumulative Distribution Functions along with Quantiles (Univariate) and Nonparametric Correlation (Bivariate)
Distributions visualized
Agnostic (re)implementations (R/SAS/Python/C) of common quantile estimation algorithms.
R package providing functions for computing Expected shortfall (ES) and Value at risk (VaR)
B-digest is a Go library for fast and memory-efficient estimation of quantiles with guaranteed relative error and full mergeability
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