<?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>epimundi.r-universe.dev</title><link>https://epimundi.r-universe.dev</link><description>Recent package updates in epimundi</description><generator>R-universe</generator><image><url>https://github.com/epimundi.png</url><title>R packages by epimundi</title><link>https://epimundi.r-universe.dev</link></image><lastBuildDate>Wed, 22 Oct 2025 12:54:11 GMT</lastBuildDate><item><title>[epimundi] andorR 0.3.1</title><author>angus.cameron@epimundi.com (Angus R Cameron)</author><description>A decision support tool to strategically prioritise
evidence gathering in complex, hierarchical AND-OR decision
trees. It is designed for situations with incomplete or
uncertain information where the goal is to reach a confident
conclusion as efficiently as possible (responding to the
minimum number of questions, and only spending resources on
generating improved evidence when it is of significant value to
the final decision). The framework excels in complex analyses
with multiple potential successful pathways to a conclusion
('OR' nodes). Key features include a dynamic influence index to
guide users to the most impactful question, a system for
propagating answers and semi-quantitative confidence scores
(0-5) up the tree, and post-conclusion guidance to identify the
best actions to increase the final confidence. These components
are brought together in an interactive command-line workflow
that guides the analysis from start to finish.</description><link>https://github.com/r-universe/epimundi/actions/runs/27864962775</link><pubDate>Wed, 22 Oct 2025 12:54:11 GMT</pubDate><r:package>andorR</r:package><r:version>0.3.1</r:version><r:status>success</r:status><r:repository>https://epimundi.r-universe.dev</r:repository><r:upstream>https://github.com/epimundi/andorr</r:upstream><r:article><r:source>confidence-boosting.Rmd</r:source><r:filename>confidence-boosting.html</r:filename><r:title>Confidence Boosting and Sensitivity Analysis</r:title><r:created>2025-09-20 14:25:45</r:created><r:modified>2025-09-28 18:56:43</r:modified></r:article><r:article><r:source>data-formats.Rmd</r:source><r:filename>data-formats.html</r:filename><r:title>Data Formats for andorR</r:title><r:created>2025-09-20 09:55:59</r:created><r:modified>2025-09-28 18:56:43</r:modified></r:article><r:article><r:source>example-data-files.Rmd</r:source><r:filename>example-data-files.html</r:filename><r:title>Example Data Files</r:title><r:created>2025-09-19 16:30:40</r:created><r:modified>2025-10-04 10:31:13</r:modified></r:article><r:article><r:source>andorR-intro.Rmd</r:source><r:filename>andorR-intro.html</r:filename><r:title>Introduction to andorR</r:title><r:created>2025-09-19 16:30:40</r:created><r:modified>2025-09-28 18:56:43</r:modified></r:article><r:article><r:source>tree-optimisation.Rmd</r:source><r:filename>tree-optimisation.html</r:filename><r:title>Optimisation of AND-OR Decision Trees</r:title><r:created>2025-09-19 16:30:40</r:created><r:modified>2025-09-28 18:56:43</r:modified></r:article></item></channel></rss>