Probabilistic Data Structures and Algorithms in Python

DynaHist: A Dynamic Histogram Library for Java

Multiple quantiles estimation model maintaining non-crossing condition (or monotone quantile condition) using LightGBM and XGBoost

C++ version of Ted Dunning's merging t-digest

Distributional Gradient Boosting Machines

An extension of Py-Boost to probabilistic modelling

A library to compute histograms on distributed environments, on streaming data

Wicked Fast, Accurate Quantiles Using 'T-Digests'

Agnostic (re)implementations (R/SAS/Python/C) of common quantile estimation algorithms.

Prometheus summary with quantiles

Monotone composite quantile regression neural network (MCQRNN) with tensorflow 2.x.

C++14 port of the DDSketch distributed quantile sketch algorithm

Python Implementation of Graham Cormode and S. Muthukrishnan's Effective Computation of Biased Quantiles over Data Streams in ICDE’05

B-digest is a Go library for fast and memory-efficient estimation of quantiles with guaranteed relative error and full mergeability

[JCGS 2021] Official Implement of the paper "Learning Multiple Quantiles With Neural Networks"

Compute least squares estimates and IVX estimates with pairwise quantile predictive regressions (R package)

A q-quantile estimator for high-dimensional distributions

Set of algorithms, used for estimation statistic characteristics on streaming data.

Some R Code for My Paper

Aioprometheus summary with quantiles