The tDigest construction algorithm, by Dunning et al., (2019) <arXiv:1902.04023v1>, uses a variant of 1dimensional kmeans clustering to produce a very compact data structure that allows accurate estimation of quantiles. This tDigest 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 tDigest over previous digests for this purpose is that the tDigest handles data with full floating point resolution. The accuracy of quantile estimates produced by tDigests can be orders of magnitude more accurate than those produced by previous digest algorithms. Methods are provided to create and update tDigests and retrieve quantiles from the accumulated distributions.
Package details 


Author  Bob Rudis [aut, cre] (<https://orcid.org/0000000156702640>), Ted Dunning [aut] (tDigest algorithm; <https://github.com/tdunning/tdigest/>), Andrew Werner [aut] (Original C+ code; <https://github.com/ajwerner/tdigest>) 
Maintainer  Bob Rudis <bob@rud.is> 
License  MIT + file LICENSE 
Version  0.3.0 
URL  https://gitlab.com/hrbrmstr/tdigest 
Package repository  View on CRAN 
Installation 
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