<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>multilevel data | Jesper N. Wulff</title><link>https://jespernwulff.github.io/tags/multilevel-data/</link><atom:link href="https://jespernwulff.github.io/tags/multilevel-data/index.xml" rel="self" type="application/rss+xml"/><description>multilevel data</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Sat, 01 Oct 2022 00:00:00 +0200</lastBuildDate><image><url>https://jespernwulff.github.io/media/icon_hu_c98bc1085d22e9da.png</url><title>multilevel data</title><link>https://jespernwulff.github.io/tags/multilevel-data/</link></image><item><title>biokNN</title><link>https://jespernwulff.github.io/software/bioknn/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://jespernwulff.github.io/software/bioknn/</guid><description>&lt;p&gt;&lt;code&gt;biokNN&lt;/code&gt; provides a bi-objective k-nearest-neighbours imputation method for multilevel data, balancing global structure and cluster-level structure when filling in missing values. It accompanies Cubillos, Wøhlk &amp;amp; Wulff (2022).&lt;/p&gt;
&lt;pre&gt;&lt;code&gt;install.packages(&amp;quot;biokNN&amp;quot;)
&lt;/code&gt;&lt;/pre&gt;</description></item><item><title>A Bi-Objective k-Nearest-Neighbors-Based Imputation Method for Multilevel Data</title><link>https://jespernwulff.github.io/publication/biknn-imputation-multilevel/</link><pubDate>Sat, 01 Oct 2022 00:00:00 +0200</pubDate><guid>https://jespernwulff.github.io/publication/biknn-imputation-multilevel/</guid><description/></item></channel></rss>