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tdigest
View on CRAN: Click
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Download and install tdigest package within the R console
Install from CRAN:
install.packages("tdigest")
Install from Github:
library("remotes")
install_github("cran/tdigest")
Install by package version:
library("remotes")
install_version("tdigest", "0.4.2")
Attach the package and use:
library("tdigest")
Maintained by
Bob Rudis
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-08-01
Latest Update: 2022-10-04
Description:
The t-Digest construction algorithm, by Dunning et al., (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.
How to cite:
Bob Rudis (2019). tdigest: Wicked Fast, Accurate Quantiles Using t-Digests. R package version 0.4.2, https://cran.r-project.org/web/packages/tdigest. Accessed 01 Feb. 2025.
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imports, suggests or enhances
Complete documentation for tdigest
Functions, R codes and Examples using
the tdigest R package
Some associated functions: as.list.tdigest . pipe . td_add . td_create . td_merge . td_quantile_of . td_total_count . td_value_at . tdigest . tquantile .
Some associated R codes: create.R . util.R . utils-pipe.R . Full tdigest package functions and examples
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