Benchmark of different quantile implementations
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Updated
Jul 5, 2017 - Java
Benchmark of different quantile implementations
A q-quantile estimator for high-dimensional distributions
A data structure for accurate on-line accumulation of rank-based statistics.
Set of algorithms, used for estimation statistic characteristics on streaming data.
Probabilistic Data Structures and Algorithms in Python
An implementation of the Greenwald-Khanna approximate quantile streaming algorithm as a Spark user-defined aggregate function.
Agnostic (re)implementations (R/SAS/Python/C) of common quantile estimation algorithms.
Streaming Quantile Calculation Algorithm
C++ version of Ted Dunning's merging t-digest
An open benchmark for real-time analytics benchmark over massive data sets
C++14 port of the DDSketch distributed quantile sketch algorithm
Working with real-world data to estimate confidence intervals of quantiles, using Bootstrap.
A library to compute histograms on distributed environments, on streaming data
R package for estimation of elliptical extreme quantile regions
Distributional Gradient Boosting Machines
B-digest is a Go library for fast and memory-efficient estimation of quantiles with guaranteed relative error and full mergeability
An extension of Py-Boost to probabilistic modelling
Monotone composite quantile regression neural network (MCQRNN) with tensorflow 2.x.
Wicked Fast, Accurate Quantiles Using 'T-Digests'
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