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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>A simple measure of conditional dependence · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1910.12327/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/1910.12327/feed.xml" rel="self" type="application/rss+xml" /><item><title>A simple measure of conditional dependence — mentioned by derbOac</title><link>https://news.ycombinator.com/item?id=29688889</link><guid isPermaLink="false">urn:hackerpapers:mention:1910.12327:29688889</guid><pubDate>Sun, 26 Dec 2021 01:41:11 GMT</pubDate><description>&lt;p&gt;Also worth looking at the cited and related paper with the same author: https://arxiv.org/abs/1910.12327 This follow-up paper presents a related measure of conditional dependence that has a &amp;quot;natural interpretation as a nonlinear generalization of the familiar partial R2 statistic for measuring conditional dependence by regression.&amp;quot; The follow-up paper also provides some additional interpretive insights, I think. My intuitive impression is that both of these are important developments. I also have a very vague suspicion, based on the form of the function, that the correlation measure has some…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1910.12327/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>math.ST</category></item></channel></rss>
