{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/computing-extremely-accurate-quantiles-using","title":"Computing Extremely Accurate Quantiles Using t-Digests","arxiv_id":"1902.04023","date":"2019-02-11","proceeding":null,"authors":["Ted Dunning","Otmar Ertl"],"abstract":"We present on-line algorithms for computing approximations of rank-based statistics that give high accuracy, particularly near the tails of a distribution, with very small sketches. Notably, the method allows a quantile $q$ to be computed with an accuracy relative to $\\max(q, 1-q)$ rather than absolute accuracy as with most other methods. This new algorithm is robust with respect to skewed distributions or ordered datasets and allows separately computed summaries to be combined with no loss in accuracy. An open-source Java implementation of this algorithm is available from the author. Independent implementations in Go and Python are also available.","url_abs":"http://arxiv.org/abs/1902.04023v1","url_pdf":"http://arxiv.org/pdf/1902.04023v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"computing-extremely-accurate-quantiles-using","repo_url":"https://github.com/tdunning/t-digest","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"computing-extremely-accurate-quantiles-using","repo_url":"https://github.com/PavelVesely/t-digest","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"computing-extremely-accurate-quantiles-using","repo_url":"https://github.com/cmip6dr/_ReviewVarRanges","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"computing-extremely-accurate-quantiles-using","repo_url":"https://github.com/signalfx/t-digest","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1902.04023","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}