<?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>kaisun84.r-universe.dev</title><link>https://kaisun84.r-universe.dev</link><description>Recent package updates in kaisun84</description><generator>R-universe</generator><image><url>https://github.com/kaisun84.png</url><title>R packages by kaisun84</title><link>https://kaisun84.r-universe.dev</link></image><lastBuildDate>Tue, 29 Sep 2026 14:20:02 GMT</lastBuildDate><item><title>[kaisun84] spscsfa 0.1.0</title><author>ksun1@shu.edu.cn (Kai Sun)</author><description>Provides semiparametric smooth-coefficient stochastic
frontier analysis following Sun and Kumbhakar (2013)
&lt;doi:10.1016/j.econlet.2013.05.001&gt; where the coefficients of
the parametric part vary smoothly with a set of nonparametric
variables. Inefficiency term is allowed to depend on a set of
determinants through heteroskedasticity. Smooth coefficients
are estimated using nonparametric regression and the remaining
frontier parameters are estimated by maximum likelihood.
Technical efficiency and inefficiency are computed using the
Battese and Coelli (1988) &lt;doi:10.1016/0304-4076(88)90053-X&gt;
and Jondrow et al. (1982) &lt;doi:10.1016/0304-4076(82)90004-5&gt;
methods, respectively. Confidence intervals for technical
efficiency are computed using the approach of Horrace and
Schmidt (1996) &lt;doi:10.1007/BF00157044&gt;.</description><link>https://github.com/r-universe/kaisun84/actions/runs/36705455958</link><pubDate>Tue, 29 Sep 2026 14:20:02 GMT</pubDate><r:package>spscsfa</r:package><r:version>0.1.0</r:version><r:status>success</r:status><r:repository>https://kaisun84.r-universe.dev</r:repository><r:upstream>https://github.com/cran/spscsfa</r:upstream></item></channel></rss>