<?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>julienforbat.r-universe.dev</title><link>https://julienforbat.r-universe.dev</link><description>Recent package updates in julienforbat</description><generator>R-universe</generator><image><url>https://github.com/julienforbat.png</url><title>R packages by julienforbat</title><link>https://julienforbat.r-universe.dev</link></image><lastBuildDate>Fri, 15 May 2026 20:24:09 GMT</lastBuildDate><item><title>[stephaneguerrier] pempi 1.0.0</title><author>stef.guerrier@gmail.com (Stéphane Guerrier)</author><description>Tools for the conditional estimation of the prevalence of
an emerging or rare infectious disease, combining a survey
sample with population-level case-count data and accounting for
measurement error. Implements the methods proposed in Guerrier,
Kuzmics and Victoria-Feser (2024)
&lt;doi:10.1080/01621459.2024.2313790&gt;. The companion paper
received the 2024 JASA Reproducibility Award.</description><link>https://github.com/r-universe/stephaneguerrier/actions/runs/38233951721</link><pubDate>Fri, 15 May 2026 20:24:09 GMT</pubDate><r:package>pempi</r:package><r:version>1.0.0</r:version><r:status>success</r:status><r:repository>https://stephaneguerrier.r-universe.dev</r:repository><r:upstream>https://github.com/stephaneguerrier/pempi</r:upstream><r:article><r:source>get_started.Rmd</r:source><r:filename>get_started.html</r:filename><r:title>Get Started</r:title><r:created>2022-05-02 11:30:44</r:created><r:modified>2026-05-15 20:21:14</r:modified></r:article><r:article><r:source>citation.Rmd</r:source><r:filename>citation.html</r:filename><r:title>How to Cite</r:title><r:created>2026-05-15 19:54:42</r:created><r:modified>2026-05-15 20:19:22</r:modified></r:article><r:article><r:source>reproducibility.Rmd</r:source><r:filename>reproducibility.html</r:filename><r:title>Results Reproducibility</r:title><r:created>2021-01-19 13:57:02</r:created><r:modified>2026-05-15 20:24:09</r:modified></r:article></item><item><title>[smac-group] simts 0.2.4</title><author>stef.guerrier@gmail.com (Stéphane Guerrier)</author><description>A system contains easy-to-use tools as a support for time
series analysis courses. In particular, it incorporates a
technique called Generalized Method of Wavelet Moments (GMWM)
as well as its robust implementation for fast and robust
parameter estimation of time series models which is described,
for example, in Guerrier et al. (2013) &lt;doi:
10.1080/01621459.2013.799920&gt;. More details can also be found
in the paper linked to via the URL below.</description><link>https://github.com/r-universe/smac-group/actions/runs/37435155826</link><pubDate>Tue, 10 Mar 2026 08:59:08 GMT</pubDate><r:package>simts</r:package><r:version>0.2.4</r:version><r:status>success</r:status><r:repository>https://smac-group.r-universe.dev</r:repository><r:upstream>https://github.com/smac-group/simts</r:upstream><r:article><r:source>vignettes.Rmd</r:source><r:filename>vignettes.html</r:filename><r:title>simts Vignettes</r:title><r:created>2017-09-08 21:21:23</r:created><r:modified>2022-09-02 08:23:37</r:modified></r:article></item><item><title>[smac-group] wv 0.1.3</title><author>stef.guerrier@gmail.com (Stéphane Guerrier)</author><description>Provides a series of tools to compute and plot quantities
related to classical and robust wavelet variance for time
series and regular lattices. More details can be found, for
example, in Serroukh, A., Walden, A.T., &amp; Percival, D.B. (2000)
&lt;doi:10.2307/2669537&gt; and Guerrier, S. &amp; Molinari, R. (2016)
&lt;doi:10.48550/arXiv.1607.05858&gt;.</description><link>https://github.com/r-universe/smac-group/actions/runs/37605377431</link><pubDate>Wed, 08 Oct 2025 08:01:41 GMT</pubDate><r:package>wv</r:package><r:version>0.1.3</r:version><r:status>success</r:status><r:repository>https://smac-group.r-universe.dev</r:repository><r:upstream>https://github.com/smac-group/wv</r:upstream></item><item><title>[smac-group] avar 0.1.2</title><author>stef.guerrier@gmail.com (Stéphane Guerrier)</author><description>Implements the allan variance and allan variance linear
regression estimator for latent time series models. More
details about the method can be found, for example, in
Guerrier, S., Molinari, R., &amp; Stebler, Y. (2016)
&lt;doi:10.1109/LSP.2016.2541867&gt;.</description><link>https://github.com/r-universe/smac-group/actions/runs/37763142482</link><pubDate>Mon, 11 Jul 2022 18:20:20 GMT</pubDate><r:package>avar</r:package><r:version>0.1.2</r:version><r:status>success</r:status><r:repository>https://smac-group.r-universe.dev</r:repository><r:upstream>https://github.com/smac-group/avar</r:upstream><r:article><r:source>avar-example.Rmd</r:source><r:filename>avar-example.html</r:filename><r:title>Allan Variance Linear Regression Estimation Examples</r:title><r:created>2018-08-21 14:50:37</r:created><r:modified>2020-01-15 18:10:30</r:modified></r:article></item></channel></rss>