From c839b06359eeb1587c06a3bd3dad2eecbed07ee9 Mon Sep 17 00:00:00 2001 From: Eric Johnson Date: Mon, 21 Aug 2023 13:12:44 -0500 Subject: [PATCH] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 3016f8e..ec2ec83 100644 --- a/README.md +++ b/README.md @@ -8,7 +8,7 @@ Email: eric.johnson643@gmail.com **E**mpirical **M**arginal resampling **B**etter **E**valuates **D**imensionality **R**eduction, or **EMBEDR**, is a method for evaluating the extent to which an embedding generated by a dimensionality reduction algorithm contains structures that are more similar to the structures in the high-dimensional space than we expect by random chance. The method applies the concept of an empirical hypothesis test, where a null distribution for a sample statistic is generated via marginal resampling, in order to estimate whether samples are better-embedded than a given DRA might do by chance. -For complete details, see our [preprint](https://www.biorxiv.org/content/10.1101/2020.11.18.389031v2). +For complete details, see our [publication](https://doi.org/10.1016/j.patter.2022.100443). ## Installation