<?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>jornlotsch.r-universe.dev</title><link>https://jornlotsch.r-universe.dev</link><description>Recent package updates in jornlotsch</description><generator>R-universe</generator><image><url>https://github.com/jornlotsch.png</url><title>R packages by jornlotsch</title><link>https://jornlotsch.r-universe.dev</link></image><lastBuildDate>Thu, 21 May 2026 08:20:26 GMT</lastBuildDate><item><title>[jornlotsch] EDOtrans 0.3.5</title><author>j.lotsch@em.uni-frankfurt.de (Jorn Lotsch)</author><description>A data transformation method which takes into account the
special property of scale non-invariance with a breakpoint at 1
of the Euclidean distance.</description><link>https://github.com/r-universe/jornlotsch/actions/runs/26283906501</link><pubDate>Thu, 21 May 2026 08:20:26 GMT</pubDate><r:package>EDOtrans</r:package><r:version>0.3.5</r:version><r:status>success</r:status><r:repository>https://jornlotsch.r-universe.dev</r:repository><r:upstream>https://github.com/jornlotsch/edotrans</r:upstream></item><item><title>[cran] VoronoiBiomedPlot 0.3.2</title><author>j.lotsch@em.uni-frankfurt.de (Jorn Lotsch)</author><description>Creates visualization plots for 2D data including ellipse
plots, Voronoi tesselation plots, and combined ellipse-Voronoi
plots. Designed to visualize class separation in 2D data, raw
of from projection techniques like principal component analysis
(PCA), partial least squares discriminant analysis (PLS-DA) or
others. For more details see Lotsch and Kringel (2026) and
Lotsch, J., and Kringel, D. (2026)
&lt;doi:10.1371/journal.pone.0333653&gt;.</description><link>https://github.com/r-universe/cran/actions/runs/26389563555</link><pubDate>Sat, 25 Apr 2026 07:48:26 GMT</pubDate><r:package>VoronoiBiomedPlot</r:package><r:version>0.3.2</r:version><r:status>success</r:status><r:repository>https://cran.r-universe.dev</r:repository><r:upstream>https://github.com/cran/VoronoiBiomedPlot</r:upstream></item><item><title>[jornlotsch] opGMMassessment 0.4.5</title><author>j.lotsch@em.uni-frankfurt.de (Jorn Lotsch)</author><description>Necessary functions for optimized automated evaluation of
the number and parameters of Gaussian mixtures in
one-dimensional data. Various methods are available for
parameter estimation and for determining the number of modes in
the mixture. A detailed description of the methods ca ben found
in Lotsch, J., Malkusch, S. and A. Ultsch. (2022)
&lt;doi:10.1016/j.imu.2022.101113&gt;.</description><link>https://github.com/r-universe/jornlotsch/actions/runs/25986855681</link><pubDate>Fri, 17 Apr 2026 10:31:45 GMT</pubDate><r:package>opGMMassessment</r:package><r:version>0.4.5</r:version><r:status>success</r:status><r:repository>https://jornlotsch.r-universe.dev</r:repository><r:upstream>https://github.com/jornlotsch/opgmmassessment</r:upstream></item><item><title>[jornlotsch] pguIMP 0.1.1</title><author>j.lotsch@em.uni-frankfurt.de (Jorn Lotsch)</author><description>Reproducible cleaning of biomedical laboratory data using
visualization, error correction, and transformation methods
implemented as interactive R notebooks. A detailed description
of the methods ca ben found in Malkusch, S., Hahnefeld, L.,
Gurke, R. and J. Lotsch. (2021) &lt;doi:10.1002/psp4.12704&gt;.</description><link>https://github.com/r-universe/jornlotsch/actions/runs/26275049757</link><pubDate>Wed, 18 Feb 2026 06:25:54 GMT</pubDate><r:package>pguIMP</r:package><r:version>0.1.1</r:version><r:status>success</r:status><r:repository>https://jornlotsch.r-universe.dev</r:repository><r:upstream>https://github.com/jornlotsch/pguimp</r:upstream></item><item><title>[jornlotsch] opImputation 0.6</title><author>j.lotsch@em.uni-frankfurt.de (Jorn Lotsch)</author><description>A model-agnostic framework for selecting dataset-specific
imputation methods for missing values in numerical data related
to pain. Lotsch J, Ultsch A (2025) &quot;A model-agnostic framework
for dataset-specific selection of missing value imputation
methods in pain-related numerical data&quot; Canadian Journal of
Pain (in minor revision).</description><link>https://github.com/r-universe/jornlotsch/actions/runs/27056614038</link><pubDate>Sat, 08 Nov 2025 06:26:54 GMT</pubDate><r:package>opImputation</r:package><r:version>0.6</r:version><r:status>success</r:status><r:repository>https://jornlotsch.r-universe.dev</r:repository><r:upstream>https://github.com/jornlotsch/opimputation</r:upstream></item><item><title>[jornlotsch] detectXOR 0.1.0</title><author>j.lotsch@em.uni-frankfurt.de (Jorn Lotsch)</author><description>Provides tools for detecting XOR-like patterns in variable
pairs in two-class data sets. Includes visualizations for
pattern exploration and reporting capabilities with both text
and HTML output formats.</description><link>https://github.com/r-universe/jornlotsch/actions/runs/27088785016</link><pubDate>Sat, 12 Jul 2025 05:39:48 GMT</pubDate><r:package>detectXOR</r:package><r:version>0.1.0</r:version><r:status>success</r:status><r:repository>https://jornlotsch.r-universe.dev</r:repository><r:upstream>https://github.com/jornlotsch/detectxor</r:upstream></item></channel></rss>