<?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>invalid-email-address.r-universe.dev</title><link>https://invalid-email-address.r-universe.dev</link><description>Recent package updates in invalid-email-address</description><generator>R-universe</generator><image><url>https://github.com/invalid-email-address.png</url><title>R packages by invalid-email-address</title><link>https://invalid-email-address.r-universe.dev</link></image><lastBuildDate>Fri, 11 Sep 2026 04:26:18 GMT</lastBuildDate><item><title>[pachadotdev] cobbdouglasge 0.0.0.9000</title><author>your@email.com (firstname lastname)</author><description>A Shiny app to visualize an Edgeworth box with contract
curve for the 2x2 exchange model using Cobb-Douglas utility
functions.</description><link>https://github.com/r-universe/pachadotdev/actions/runs/38122122721</link><pubDate>Fri, 11 Sep 2026 04:26:18 GMT</pubDate><r:package>cobbdouglasge</r:package><r:version>0.0.0.9000</r:version><r:status>success</r:status><r:repository>https://pachadotdev.r-universe.dev</r:repository><r:upstream>https://github.com/pachadotdev/cobbdouglasge</r:upstream></item><item><title>[yosleycarrero2025] wordorientation 0.1.0</title><author>you@example.com (Your Name)</author><description>Provides tools to quantify how strongly pairs of words
attract or repel each other in a text corpus, based on
co-occurrence patterns. For each word pair, the phi coefficient
(a correlation measure for binary variables) is computed from a
document-term matrix and tested for significance, then
classified as showing attraction (co-occurring more than chance
would predict), repulsion (co-occurring less than chance would
predict), or no significant relationship. A full pipeline is
provided from raw text to a labeled network visualization.
Unlike general-purpose pairwise correlation tools,
'wordorientation' is built specifically for text: it handles
tokenization and stopword removal, applies significance-based
classification rather than reporting a raw correlation
coefficient alone, and produces a ready-to-plot attraction/
repulsion network. Methods for word co-occurrence and the phi
coefficient follow Evert (2008) &lt;doi:10.1075/z.143.13eve&gt; and
standard corpus linguistics practice for collocation and
association measures.</description><link>https://github.com/r-universe/yosleycarrero2025/actions/runs/36234145180</link><pubDate>Thu, 27 Aug 2026 18:51:01 GMT</pubDate><r:package>wordorientation</r:package><r:version>0.1.0</r:version><r:status>success</r:status><r:repository>https://yosleycarrero2025.r-universe.dev</r:repository><r:upstream>https://github.com/yosleycarrero2025/wordorientation</r:upstream></item><item><title>[phanthomx] finRiskPractical 0.1.0</title><author>you@example.com (Phanthomx)</author><description>A collection of ten worked practical scripts covering R
fundamentals, term structure modelling, market risk (VaR),
credit risk (Markov chains), operational risk
(frequency-severity models), volatility (GARCH), portfolio
optimisation, Monte Carlo risk simulation, and a Shiny risk
dashboard. Each Practical*() function prints the annotated R
code for that topic so it can be copied, run, and studied
interactively. This package intentionally ships the material as
printable teaching code rather than as executed computations,
so it has no hard dependency on the packages used inside the
printed examples (minpack.lm, evd, rugarch, quadprog, shiny);
install those separately if you want to run the printed code
yourself.</description><link>https://github.com/r-universe/phanthomx/actions/runs/36848196605</link><pubDate>Fri, 03 Jul 2026 20:20:49 GMT</pubDate><r:package>finRiskPractical</r:package><r:version>0.1.0</r:version><r:status>success</r:status><r:repository>https://phanthomx.r-universe.dev</r:repository><r:upstream>https://github.com/phanthomx/finRiskPractical</r:upstream></item><item><title>[kubdatalab] ggdatalab 0.1.1</title><author>you@example.com (Christian Knudsen)</author><description>A ggplot2 extension providing a Datalab theme and colour
scales.</description><link>https://github.com/r-universe/kubdatalab/actions/runs/39014690423</link><pubDate>Fri, 19 Dec 2025 13:25:45 GMT</pubDate><r:package>ggdatalab</r:package><r:version>0.1.1</r:version><r:status>success</r:status><r:repository>https://kubdatalab.r-universe.dev</r:repository><r:upstream>https://github.com/KUBDatalab/ggdatalab</r:upstream><r:article><r:source>using-ggdatalab.Rmd</r:source><r:filename>using-ggdatalab.html</r:filename><r:title>Using ggdatalab</r:title><r:created>2025-12-19 12:17:01</r:created><r:modified>2025-12-19 12:17:01</r:modified></r:article></item><item><title>[jayarasan] simIC 0.1.0</title><author>your@email.com (Jayanthi Arasan)</author><description>Provides tools to simulate and analyze interval-censored
survival data, including left-, right-, and uncensored cases,
under common parametric distributions such as Weibull,
Exponential, Log-Normal, Log-Logistic, Gamma, Gompertz, Normal,
Logistic, and EMV. The package supports both direct maximum
likelihood estimation and imputation-based approaches, making
it suitable for methodological research, benchmarking, and
teaching purposes. An interactive web-based companion tool is
also available.</description><link>https://github.com/r-universe/jayarasan/actions/runs/35712822199</link><pubDate>Tue, 29 Jul 2025 03:48:16 GMT</pubDate><r:package>simIC</r:package><r:version>0.1.0</r:version><r:status>success</r:status><r:repository>https://jayarasan.r-universe.dev</r:repository><r:upstream>https://github.com/jayarasan/simic</r:upstream></item><item><title>[m-murphy] eppicenter.tools 0.0.0.9000</title><author>your@email.com (firstname lastname)</author><description>What the package does (one paragraph).</description><link>https://github.com/r-universe/m-murphy/actions/runs/38370022468</link><pubDate>Fri, 17 May 2024 16:07:37 GMT</pubDate><r:package>eppicenter.tools</r:package><r:version>0.0.0.9000</r:version><r:status>success</r:status><r:repository>https://m-murphy.r-universe.dev</r:repository><r:upstream>https://github.com/m-murphy/eppicenter.tools</r:upstream></item></channel></rss>