<?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>nasyazahira.r-universe.dev</title><link>https://nasyazahira.r-universe.dev</link><description>Recent package updates in nasyazahira</description><generator>R-universe</generator><image><url>https://github.com/nasyazahira.png</url><title>R packages by nasyazahira</title><link>https://nasyazahira.r-universe.dev</link></image><lastBuildDate>Wed, 03 Sep 2025 06:11:24 GMT</lastBuildDate><item><title>[nasyazahira] saeHB.TF.beta 0.2.0</title><author>nasyazp28@gmail.com (Nasya Zahira Putri)</author><description>Estimates area and subarea level proportions using the
Small Area Estimation (SAE) Twofold Subarea Model with a
hierarchical Bayesian (HB) approach under Beta distribution. A
number of simulated datasets generated for illustration
purposes are also included. The 'rstan' package is employed to
estimate parameters via the Hamiltonian Monte Carlo and No
U-Turn Sampler algorithm. The model-based estimators include
the HB mean, the variation of the mean, and quantiles. For
references, see Rao and Molina (2015)
&lt;doi:10.1002/9781118735855&gt;, Torabi and Rao (2014)
&lt;doi:10.1016/j.jmva.2014.02.001&gt;, Leyla Mohadjer et al.(2007)
&lt;http://www.asasrms.org/Proceedings/y2007/Files/JSM2007-000559.pdf&gt;,
Erciulescu et al.(2019) &lt;doi:10.1111/rssa.12390&gt;, and Yudasena
(2024).</description><link>https://github.com/r-universe/nasyazahira/actions/runs/25853754588</link><pubDate>Wed, 03 Sep 2025 06:11:24 GMT</pubDate><r:package>saeHB.TF.beta</r:package><r:version>0.2.0</r:version><r:status>success</r:status><r:repository>https://nasyazahira.r-universe.dev</r:repository><r:upstream>https://github.com/nasyazahira/saehb.tf.beta</r:upstream><r:article><r:source>saeHB-Twofold-Beta.Rmd</r:source><r:filename>saeHB-Twofold-Beta.html</r:filename><r:title>saeHB-Twofold-Beta</r:title><r:created>2025-07-01 15:50:40</r:created><r:modified>2025-09-03 06:11:24</r:modified></r:article></item></channel></rss>