tdigest
0.4.3Wicked Fast, Accurate Quantiles Using t-Digests
Overview
The t-Digest construction algorithm, by Dunning, (2019) doi:10.48550/arXiv.1902.04023, uses a variant of 1-dimensional k-means clustering to produce a very compact data structure that allows accurate estimation of quantiles. This t-Digest data structure can be used to estimate quantiles, compute other rank statistics or even to estimate related measures like trimmed means. The advantage of the t-Digest over previous digests for this purpose is that the t-Digest handles data with full floating point resolution. The accuracy of quantile estimates produced by t-Digests can be orders of magnitude more accurate than those produced by previous digest algorithms. Methods are provided to create and update t-Digests and retrieve quantiles from the accumulated distributions.
Install
Health
- OK2026-05-067 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 89%
- Return-value docs
- 89%
- References docs
- 30%
Downloads
Repository
Repository practices
Repository git.sr.ht/~hrbrmstr/tdigest is linked, but repository-practices checks have not run for it yet. Checks are GitHub-only for now.
Dependencies
Nothing depends on this yet.
Code & Tests
- Cyclomatic complexity
- 1.0 median / 4 max
- Test cases
- 23 / 0.29 per code line
Test coverage
Line coverage
76%
Expression
77.7%
Tests / Examples
75.9% / 69% ex
Functions
54 10 exported
Complexity
1.5 avg / 4 max
Call network
54 nodes / 49 edges
Call graph
Open call graph →Lowest coverage
54 functions| Function | Cyclo | Coverage |
|---|---|---|
| td_merge exp | 1 | 0% |
| print.tdigest | 2 | 0% |
| [.tdigest | 4 | 50% |
| is_tdigest exp | 3 | 67% |
| tquantile exp | 2 | 75% |
| as_tdigest exp | 1 | 100% |
People & History
4 releases. Pick two to compare their code metrics. R releases are shown for context.
- 0.4.3Latest
- unarchivedReturned to CRAN2026-05-05
- RR 4.6.0 released · 2026-04-24
- archivedRemoved from CRAN2026-02-07issues were not corrected despite reminders
- RR 4.5.0 released · 2025-04-11
- 0.4.22024-06-19 · diff ↗
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 0.4.12022-10-04 · diff ↗
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- 0.3.02019-08-01
- RR 3.6.0 released · 2019-04-26
Package metadata
- First published
- 2026-05-05
- Total releases
- 4 / 1 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.5.0
- Download size
- not tracked yet
- Installed size
- not tracked yet
- With dependencies
- not tracked yet