<?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>sagnikbhadury.r-universe.dev</title><link>https://sagnikbhadury.r-universe.dev</link><description>Recent package updates in sagnikbhadury</description><generator>R-universe</generator><image><url>https://github.com/sagnikbhadury.png</url><title>R packages by sagnikbhadury</title><link>https://sagnikbhadury.r-universe.dev</link></image><lastBuildDate>Wed, 16 Sep 2026 15:48:40 GMT</lastBuildDate><item><title>[sagnikbhadury] ISPAT3D 0.3.1</title><author>bhadury@umich.edu (Sagnik Bhadury)</author><description>Fits tumor-zone-specific conditional cell-density networks
from registered three-dimensional multiplex imaging. An
anisotropic Matern-3/2 Gaussian process is estimated per
variable and zone using a Vecchia likelihood on spatially
balanced anchors; predictions at all selected cells yield
residual covariance sufficient statistics. Gaussian maximum
likelihood then fits a shared-plus-zone factor covariance
model. A matched section-wise planar fit uses the same selected
cells and covariance estimator. This extends the spatially
informed cell-density analysis of Bhadury et al. (2026)
&lt;doi:10.1038/s41598-026-35341-8&gt;.</description><link>https://github.com/r-universe/sagnikbhadury/actions/runs/36411779792</link><pubDate>Wed, 16 Sep 2026 15:48:40 GMT</pubDate><r:package>ISPAT3D</r:package><r:version>0.3.1</r:version><r:status>success</r:status><r:repository>https://sagnikbhadury.r-universe.dev</r:repository><r:upstream>https://github.com/sagnikbhadury/ispat-3d</r:upstream><r:article><r:source>volumetric-network.Rmd</r:source><r:filename>volumetric-network.html</r:filename><r:title>A volumetric cell-density network from a small registered image</r:title><r:created>2026-09-16 15:24:30</r:created><r:modified>2026-09-16 15:24:30</r:modified></r:article><r:article><r:source>matched-planar-network.Rmd</r:source><r:filename>matched-planar-network.html</r:filename><r:title>Matched section-wise 2D networks and a 3D comparison</r:title><r:created>2026-09-16 15:24:30</r:created><r:modified>2026-09-16 15:24:30</r:modified></r:article></item></channel></rss>