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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Learning as We Go: An Examination of the Statistical Accuracy of COVID19 Daily Death Count Predictions · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2004.04734/</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/2004.04734/feed.xml" rel="self" type="application/rss+xml" /><item><title>Learning as We Go: An Examination of the Statistical Accuracy of COVID19 Daily Death Count Predictions — mentioned by icelancer</title><link>https://news.ycombinator.com/item?id=22918366</link><guid isPermaLink="false">urn:hackerpapers:mention:2004.04734:22918366</guid><pubDate>Sun, 19 Apr 2020 20:01:54 GMT</pubDate><description>&lt;p&gt;Correct. This appeal to authority fallacy being touted has given us models like the UW-IHME model which is a complete disaster in both results and in methodology. And domestic policy is being based off these models that have two orders of magnitude (at least) of absolute error, and were outside their 95% CI over half of the time. This is unacceptable. https://twitter.com/ElonBachman/status/1248649785655078914 https://arxiv.org/abs/2004.04734&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2004.04734/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>stat.OT</category></item></channel></rss>
