<?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>erincr.r-universe.dev</title><link>https://erincr.r-universe.dev</link><description>Recent package updates in erincr</description><generator>R-universe</generator><image><url>https://github.com/erincr.png</url><title>R packages by erincr</title><link>https://erincr.r-universe.dev</link></image><lastBuildDate>Fri, 16 Oct 2026 20:22:20 GMT</lastBuildDate><item><title>[erincr] ptLasso 1.0.2</title><author>ercr@umich.edu (Erin Craig)</author><description>Implements lasso pretraining for generalized linear models
for data with grouped observations; data without grouped
observations, but with multinomial responses; data with
multiple Gaussian responses; and data with repeated
measurements over time. The method fits a lasso model to an
initial dataset and then uses its support and coefficient
values to guide model fitting for a related task, which can
improve performance by leveraging larger datasets and preserve
interpretability by identifying features which are generally
shared, and which are task specific. See Craig et al. (2026)
&lt;doi:10.1093/jrsssb/qkaf050&gt; for details. Model fitting in this
package is done with cv.glmnet() from the 'glmnet' package, and
syntax closely follows that of 'glmnet' (Friedman, Hastie and
Tibshirani (2010) &lt;doi:10.18637/jss.v033.i01&gt;).</description><link>https://github.com/r-universe/erincr/actions/runs/40680001006</link><pubDate>Fri, 16 Oct 2026 20:22:20 GMT</pubDate><r:package>ptLasso</r:package><r:version>1.0.2</r:version><r:status>success</r:status><r:repository>https://erincr.r-universe.dev</r:repository><r:upstream>https://github.com/erincr/ptlasso</r:upstream><r:article><r:source>InputGroupedData.Rmd</r:source><r:filename>InputGroupedData.html</r:filename><r:title>Input grouped data</r:title><r:created>2024-06-19 02:12:21</r:created><r:modified>2025-08-26 17:22:56</r:modified></r:article><r:article><r:source>MultiResponseGaussian.Rmd</r:source><r:filename>MultiResponseGaussian.html</r:filename><r:title>Multi-response data with Gaussian responses</r:title><r:created>2024-06-13 19:31:35</r:created><r:modified>2025-08-26 17:22:56</r:modified></r:article><r:article><r:source>ptLasso.Rmd</r:source><r:filename>ptLasso.html</r:filename><r:title>ptLasso Vignette and Manual</r:title><r:created>2024-04-03 00:36:59</r:created><r:modified>2025-08-26 18:59:27</r:modified></r:article><r:article><r:source>TargetGroupedData.Rmd</r:source><r:filename>TargetGroupedData.html</r:filename><r:title>Target grouped or multinomial reponse data</r:title><r:created>2024-06-19 02:12:21</r:created><r:modified>2024-06-27 01:41:56</r:modified></r:article><r:article><r:source>TimeSeriesData.Rmd</r:source><r:filename>TimeSeriesData.html</r:filename><r:title>Time series data</r:title><r:created>2024-04-03 00:36:59</r:created><r:modified>2024-06-19 21:09:40</r:modified></r:article></item></channel></rss>