Probabilistic Data Structures and Algorithms in Python

DynaHist: A Dynamic Histogram Library for Java

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

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

Distributional Gradient Boosting Machines

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

An extension of Py-Boost to probabilistic modelling

Wicked Fast, Accurate Quantiles Using 'T-Digests'

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

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

Prometheus summary with quantiles

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

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

Aioprometheus summary with quantiles

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

Some R Code for My Paper

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

A data structure for accurate on-line accumulation of rank-based statistics.

A q-quantile estimator for high-dimensional distributions