AlexanderSaydakov commented on code in PR #58: URL: https://github.com/apache/datasketches-python/pull/58#discussion_r1917461209
########## docs/source/quantiles/tdigest.rst: ########## @@ -0,0 +1,50 @@ +t-digest +-------- + +.. currentmodule:: datasketches + +The implementation in this library is based on the MergingDigest described in +`Computing Extremely Accurate Quantiles Using t-Digests <https://arxiv.org/abs/1902.04023>`_ by Ted Dunning and Otmar Ertl. + +The implementation in this library has a few differences from the reference implementation associated with that paper: + +* Merge does not modify the input +* Derialization similar to other sketches in this library, although reading the reference implementation format is supported + +Unlike all other algorithms in the library, t-digest is empirical and has no mathematical basis for estimating its error +and its results are dependent on the input data. However, for many common data distributions, it can produce excellent results. +t-digest also operates only on numeric data and, unlike the the quantiles family algorithms in the library which return quantile Review Comment: double "the" -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: dev-unsubscr...@datasketches.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@datasketches.apache.org For additional commands, e-mail: dev-h...@datasketches.apache.org
