{"url":"/method/nlsig","slug":"nlsig","name":"NLSIG","full_name":"nlogistic-sigmoid function","full_name_withheld":false,"description_markdown":"Nlogistic-sigmoid function (NLSIG) is a modern logistic-sigmoid function definition for modelling growth (or decay) processes. It features two logistic metrics (YIR and XIR) for monitoring growth from a two-dimensional (x-y axis) perspective.","description_state":"present","introduced_year":null,"introduced_by":{"title":null,"paper":null,"first_author":null,"n_authors":0,"url_abs":null,"archive_paper_url":null},"source":{"url":null,"title":null,"url_on_a_paper_host":false},"code_snippet_url":"https://github.com/somefunAgba/NLSIG_COVID19Lab","code_snippet_url_on_a_code_host":true,"categories":[{"area":"General","area_id":"general","collection":"Activation Functions","url":"/methods/category/activation-functions","pwc_aliases":[]}],"n_papers_tagged":1,"archive_num_papers":null,"papers_newest_first":[{"paper":"/paper/the-nlogistic-sigmoid-function","title":"From the logistic-sigmoid to nlogistic-sigmoid: modelling the COVID-19 pandemic growth","date":"2020-08-06","arxiv_id":"2008.04210","n_code_links":1,"syntology":null}],"papers_shown":1,"tasks":[{"task":"/task/covid-19-modelling","name":"COVID-19 Modelling","papers":1},{"task":"/task/time-series-1","name":"Time Series","papers":1},{"task":"/task/time-series","name":"Time Series Analysis","papers":1}],"tasks_shown":3,"n_tasks":3,"usage_by_year":[{"year":"2020","papers":1}],"row_source":"embedded","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/nlsig"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}