{"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/an-o-n-method-of-calculating-kendall","title":"An O(n) method of calculating Kendall correlations of spike trains","arxiv_id":"1806.02893","date":"2020-02-25","proceeding":null,"authors":[],"abstract":"The ability to record from increasingly large numbers of neurons, and the\nincreasing attention being paid to large scale neural network simulations,\ndemands computationally fast algorithms to compute relevant statistical\nmeasures. We present an O(n) algorithm for calculating the Kendall correlation\nof spike trains, a correlation measure that is becoming especially recognized\nas an important tool in neuroscience. We show that our method is around 50\ntimes faster than the O (n ln n) method which is a current standard for quickly\ncomputing the Kendall correlation. In addition to providing a faster algorithm,\nwe emphasize the role that taking the specific nature of spike trains had on\nreducing the run time. We imagine that there are many other useful algorithms\nthat can be even more significantly sped up when taking this into\nconsideration. A MATLAB function executing the method described here has been\nmade freely available on-line.","url_abs":"http://arxiv.org/abs/1806.02893v3","url_pdf":"http://arxiv.org/pdf/1806.02893v3.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":"abstracts"},"code_links":[{"paper_slug":"an-o-n-method-of-calculating-kendall","repo_url":"https://github.com/william-redman/Kendall-Correlation-for-Large-Spike-Trains","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}