<?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>jzeuzs.r-universe.dev</title><link>https://jzeuzs.r-universe.dev</link><description>Recent package updates in jzeuzs</description><generator>R-universe</generator><image><url>https://github.com/jzeuzs.png</url><title>R packages by jzeuzs</title><link>https://jzeuzs.r-universe.dev</link></image><lastBuildDate>Fri, 30 Jan 2026 10:13:48 GMT</lastBuildDate><item><title>[jzeuzs] SemiparMF 1.0.0</title><author>mail@j3z.dev (Jezzu Morrisen Quimosing)</author><description>Fits a semiparametric spatiotemporal model for data with
mixed frequencies, specifically where the response variable is
observed at a lower frequency than some covariates. The
estimation uses an iterative backfitting algorithm that
combines a non-parametric smoothing spline for high-frequency
data, parametric estimation for low-frequency and spatial
neighborhood effects, and an autoregressive error structure.
Methodology based on Malabanan, Lansangan, and Barrios (2022)
&lt;https://scienggj.org/2022/SciEnggJ%202022-vol15-no02-p90-107-Malabanan%20et%20al.pdf&gt;.</description><link>https://github.com/r-universe/jzeuzs/actions/runs/26937437671</link><pubDate>Fri, 30 Jan 2026 10:13:48 GMT</pubDate><r:package>SemiparMF</r:package><r:version>1.0.0</r:version><r:status>success</r:status><r:repository>https://jzeuzs.r-universe.dev</r:repository><r:upstream>https://github.com/jzeuzs/semiparmf</r:upstream></item></channel></rss>