Package: tdigest 0.4.3

Bob Rudis

tdigest: Wicked Fast, Accurate Quantiles Using t-Digests

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.

Authors:Bob Rudis [aut, cre], Ted Dunning [aut], Andrew Werner [aut]

tdigest_0.4.3.tar.gz
tdigest_0.4.3.tar.gz(r-4.7-arm64)tdigest_0.4.3.tar.gz(r-4.7-x86_64)tdigest_0.4.3.tar.gz(r-4.6-arm64)tdigest_0.4.3.tar.gz(r-4.6-x86_64)
tdigest_0.4.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
tdigest/json (API)

# Install 'tdigest' in R:
install.packages('tdigest', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 665 downloads 11 exports 1 dependencies

Last updated from:921bf4e4b2. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK103
linux-devel-x86_64OK112
source / vignettesOK157
linux-release-arm64OK115
linux-release-x86_64OK109
wasm-releaseOK100

Exports:%>%as_tdigestis_tdigesttd_addtd_createtd_mergetd_quantile_oftd_total_counttd_value_attdigesttquantile

Dependencies:magrittr