<?xml version="1.0" encoding="utf-8" ?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:r="https://r-universe.dev"><channel><title>simonfreyaldenhoven.r-universe.dev</title><link>https://simonfreyaldenhoven.r-universe.dev</link><description>Recent package updates in simonfreyaldenhoven</description><generator>R-universe</generator><image><url>https://github.com/simonfreyaldenhoven.png</url><title>R packages by simonfreyaldenhoven</title><link>https://simonfreyaldenhoven.r-universe.dev</link></image><lastBuildDate>Tue, 20 Jan 2026 14:49:18 GMT</lastBuildDate><item><title>[simonfreyaldenhoven] plausibounds 1.0.1</title><author>kobleary@gmail.com (Ryan Kobler)</author><description>Enhances dynamic effect plots as suggested in
Freyaldenhoven and Hansen (2026)
&lt;https://simonfreyaldenhoven.github.io/papers/Plausible_bounds.pdf&gt;.
Data-driven smoothing delivers a smooth estimated path with
potentially improved point estimation properties and confidence
regions covering a surrogate that can be substantially tighter
than conventional pointwise or uniform bands.</description><link>https://github.com/r-universe/simonfreyaldenhoven/actions/runs/27867639601</link><pubDate>Tue, 20 Jan 2026 14:49:18 GMT</pubDate><r:package>plausibounds</r:package><r:version>1.0.1</r:version><r:status>success</r:status><r:repository>https://simonfreyaldenhoven.r-universe.dev</r:repository><r:upstream>https://github.com/simonfreyaldenhoven/plausibounds</r:upstream><r:article><r:source>documentation.Rmd</r:source><r:filename>documentation.html</r:filename><r:title>Introduction to plausibounds: Computing Plausible Bounds for dynamic effect plots</r:title><r:created>2026-01-13 20:02:21</r:created><r:modified>2026-01-20 14:49:18</r:modified></r:article></item><item><title>[simonfreyaldenhoven] l1rotation 1.0.2</title><author>kobleary@gmail.com (Ryan Kobler)</author><description>Simplify the loading matrix in factor models using the l1
criterion as proposed in Freyaldenhoven (2025)
&lt;doi:10.21799/frbp.wp.2020.25&gt;. Given a data matrix, find the
rotation of the loading matrix with the smallest l1-norm and/or
test for the presence of local factors with main function
local_factors().</description><link>https://github.com/r-universe/simonfreyaldenhoven/actions/runs/27755064893</link><pubDate>Thu, 21 Aug 2025 17:34:24 GMT</pubDate><r:package>l1rotation</r:package><r:version>1.0.2</r:version><r:status>success</r:status><r:repository>https://simonfreyaldenhoven.r-universe.dev</r:repository><r:upstream>https://github.com/simonfreyaldenhoven/l1rotation</r:upstream><r:article><r:source>documentation.Rmd</r:source><r:filename>documentation.html</r:filename><r:title>Getting Started</r:title><r:created>2025-03-26 18:22:58</r:created><r:modified>2025-05-13 15:37:39</r:modified></r:article></item></channel></rss>