tdigest: On-line accumulation of rank-based statistics

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A new data structure for accurate on-line accumulation of rank-based statistics such as quantiles and trimmed means.

See original paper: "Computing extremely accurate quantiles using t-digest" by Ted Dunning and Otmar Ertl for more details https://github.com/tdunning/t-digest/blob/07b8f2ca2be8d0a9f04df2feadad5ddc1bb73c88/docs/t-digest-paper/histo.pdf.


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Properties

Versions 0, 0.1, 0.2, 0.2.1, 0.2.1.1, 0.2.1.1, 0.3
Change log CHANGELOG.md
Dependencies base (>=4.7 && <4.15), base-compat (>=0.10.1 && <0.12), binary (>=0.7.1.0 && <0.10), deepseq (>=1.3.0.2 && <1.5), reducers (>=3.12.2 && <3.13), semigroupoids (>=5.2.2 && <5.4), semigroups (>=0.18.4 && <0.20), transformers (>=0.3 && <0.6), vector (>=0.12.0.1 && <0.13), vector-algorithms (>=0.7.0.1 && <0.9) [details]
License BSD-3-Clause
Author Oleg Grenrus <oleg.grenrus@iki.fi>
Maintainer Oleg Grenrus <oleg.grenrus@iki.fi>
Category Numeric
Home page https://github.com/phadej/haskell-tdigest#readme
Bug tracker https://github.com/phadej/haskell-tdigest/issues
Source repo head: git clone https://github.com/phadej/haskell-tdigest(tdigest)
Uploaded by phadej at 2021-01-01T17:12:31Z

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Readme for tdigest-0.2.1.1

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tdigest

A new data structure for accurate on-line accumulation of rank-based statistics such as quantiles and trimmed means.

See original paper: "Computing extremely accurate quantiles using t-digest" by Ted Dunning and Otmar Ertl

Synopsis

λ *Data.TDigest > median (tdigest [1..1000] :: TDigest 3)
Just 499.0090729817737

Benchmarks

Using 50M exponentially distributed numbers:

Example histogram

tdigest-simple -m tdigest -d standard -s 100000 -c 10 -o output.svg -i 34
cp output.svg example.svg
inkscape --export-png=example.png --export-dpi=80 --export-background-opacity=0 --without-gui example.svg

Example