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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Assessing significance in a Markov chain without mixing · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1608.02014/</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/1608.02014/feed.xml" rel="self" type="application/rss+xml" /><item><title>Assessing significance in a Markov chain without mixing — mentioned by tantalor</title><link>https://news.ycombinator.com/item?id=15961033</link><guid isPermaLink="false">urn:hackerpapers:mention:1608.02014:15961033</guid><pubDate>Tue, 19 Dec 2017 15:56:13 GMT</pubDate><description>&lt;p&gt;Article mentions the efficiency gap metric; here is another: &amp;quot;Assessing significance in a Markov chain without mixing&amp;quot; We present a new statistical test to detect that a presented state of a reversible Markov chain was not chosen from a stationary distribution... We illustrate the use of our test with a potential application to the rigorous detection of gerrymandering in Congressional districtings. https://arxiv.org/abs/1608.02014&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1608.02014/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>math.PR</category></item></channel></rss>
