<?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>rickchen0910.r-universe.dev</title><link>https://rickchen0910.r-universe.dev</link><description>Recent package updates in rickchen0910</description><generator>R-universe</generator><image><url>https://github.com/rickchen0910.png</url><title>R packages by rickchen0910</title><link>https://rickchen0910.r-universe.dev</link></image><lastBuildDate>Thu, 11 Jun 2026 18:56:07 GMT</lastBuildDate><item><title>[rickchen0910] pvarife 0.1.2</title><author>binzhi.chen9@gmail.com (Binzhi Chen)</author><description>Implements the estimator of Tugan (2021)
&lt;doi:10.1093/ectj/utaa021&gt; for panel vector autoregression
(VAR) models with interactive fixed effects. Provides joint
estimation of VAR coefficients, latent common factors, and
factor loadings via an iterative algorithm that alternates
between principal component estimation of the factors and least
squares estimation of the VAR coefficients, following the
approach of Bai (2009) &lt;doi:10.3982/ECTA6135&gt;. Supports impulse
response functions under recursive (Cholesky) identification,
parametric confidence bands from the joint asymptotic
distribution of the estimator (Theorem 2.3), and a classical
residual bootstrap for robustness checks.</description><link>https://github.com/r-universe/rickchen0910/actions/runs/27414910083</link><pubDate>Thu, 11 Jun 2026 18:56:07 GMT</pubDate><r:package>pvarife</r:package><r:version>0.1.2</r:version><r:status>success</r:status><r:repository>https://rickchen0910.r-universe.dev</r:repository><r:upstream>https://github.com/rickchen0910/pvarife</r:upstream><r:article><r:source>pvarife-quickstart.Rmd</r:source><r:filename>pvarife-quickstart.html</r:filename><r:title>Getting Started with pvarife</r:title><r:created>2026-05-31 19:14:56</r:created><r:modified>2026-05-31 19:14:56</r:modified></r:article></item><item><title>[rickchen0910] xtife 0.1.4</title><author>binzhi.chen9@gmail.com (Binzhi Chen)</author><description>Implements the interactive fixed effects ('IFE') panel
estimator of Bai (2009) &lt;doi:10.3982/ECTA6135&gt; with analytical
standard errors ('homoskedastic', 'HC1' robust, and
cluster-robust by unit). Supports asymptotic bias correction
for large panels (Bai 2009) and a dynamic extension for
predetermined regressors (Moon and Weidner 2017
&lt;doi:10.1017/S0266466615000328&gt;). Includes
information-criterion-based factor number selection (Bai and Ng
2002 &lt;doi:10.1111/1468-0262.00273&gt;). Also implements an
unbalanced panel extension using the expectation-maximisation
algorithm of Bai (2009) with exact inferential statistics from
Su, Wang and Wang (2025) &lt;doi:10.2139/ssrn.5177283&gt;, including
nuclear-norm regularisation initialisation, singular value
thresholding for factor number selection, and analytical bias
correction for both strictly and weakly exogenous regressors.
All computations use base R only with no external dependencies.</description><link>https://github.com/r-universe/rickchen0910/actions/runs/27120866673</link><pubDate>Sat, 02 May 2026 22:18:45 GMT</pubDate><r:package>xtife</r:package><r:version>0.1.4</r:version><r:status>success</r:status><r:repository>https://rickchen0910.r-universe.dev</r:repository><r:upstream>https://github.com/rickchen0910/xtife</r:upstream><r:article><r:source>xtife-introduction.Rmd</r:source><r:filename>xtife-introduction.html</r:filename><r:title>Interactive Fixed Effects for Balanced and Unbalanced Panels</r:title><r:created>2026-03-11 11:25:27</r:created><r:modified>2026-05-02 00:37:06</r:modified></r:article></item></channel></rss>