From 50373e6a8c9ed4176328140f1d4d0559769f89fc Mon Sep 17 00:00:00 2001 From: Johannes Keyser <johannes.keyser@sport.uni-giessen.de> Date: Thu, 24 Mar 2022 19:11:57 +0100 Subject: [PATCH] More final polish of documentation. --- README.md | 16 +++++++++------- 1 file changed, 9 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index 38e28a5..2d40a61 100644 --- a/README.md +++ b/README.md @@ -4,18 +4,18 @@ A stand-alone Theil-Sen estimator for robust simple regression in Matlab. -(Stand-alone: No toolbox required.) +("Stand-alone" means that no toolbox is required.) ### Theil-Sen estimator -A [Theil-Sen estimator](https://en.wikipedia.org/wiki/Theil%E2%80%93Sen_estimator) provides robust, simple linear regression in the 2D plane: +A [Theil-Sen estimator](https://en.wikipedia.org/wiki/Theil%E2%80%93Sen_estimator) provides robust linear regression for one predictor: The resulting estimates of slope and intercept are relatively insensitive to outliers. -The implementation of [TheilSen.m](TheilSen.m) is exact but naïve: +The implementation in [TheilSen.m](TheilSen.m) is exact but naïve: It generates the set of all pairs of the _n_ input samples, resulting in an overall complexity of _O(n²)_ in speed and space. The resulting slope and offset are the median slope and offset of the lines defined by all data point pairs. -(Note that alternative implementations of the algorithm have lower complexity, and thus much faster for large amounts of input samples.) +(Note that alternative implementations of the algorithm have lower complexity, and are thus much faster for large amounts of input samples.) ### No toolbox required @@ -23,8 +23,8 @@ This code is based on [Theil-Sen Robust Linear Regression](https://mathworks.com A key modification is to use `median(X, 'omitnan')` instead of `nanmedian(X)` to avoid dependency on the (commercially licensed) [Statistics Toolbox](https://mathworks.com/products/statistics.html). See the [changelog](#changelog) below for further modifications. -(Note that there are several other implementations of the Theil-Sen estimator on Mathworks's [File Exchange](https://mathworks.com/matlabcentral/fileexchange). -Unfortunately all were found to depend on the Statistics Toolbox, [except one](https://mathworks.com/matlabcentral/fileexchange/43135-regression-utilities), which was judged to be slower and less versatile.) +(Note that there are several other implementations on Mathworks's [File Exchange](https://mathworks.com/matlabcentral/fileexchange). +Unfortunately most were found to depend on the Statistics Toolbox, [except one](https://mathworks.com/matlabcentral/fileexchange/43135-regression-utilities), which was judged to be slower and less versatile.) ## Installation @@ -51,7 +51,9 @@ Note how a few "unlucky" outliers can bias the least squares estimate (LS), but ## Contributing and project status -This project is relatively unmaintained, and only shared as-is in the hope to be helpful. +This project is relatively unmaintained. +It is shared as-is in the hope to be helpful (see [license.txt](license.txt) for legal terms). + If you find a bug, feel free to let the author(s) know. Feature requests should be directed to the original author (see below). -- GitLab