<?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>santosharathod.r-universe.dev</title><link>https://santosharathod.r-universe.dev</link><description>Recent package updates in santosharathod</description><generator>R-universe</generator><image><url>https://github.com/santosharathod.png</url><title>R packages by santosharathod</title><link>https://santosharathod.r-universe.dev</link></image><lastBuildDate>Wed, 29 Apr 2026 09:30:49 GMT</lastBuildDate><item><title>[santosharathod] rgbIndices 0.1.1</title><author>santoshagriculture@gmail.com (Santosha Rathod)</author><description>Computes RGB-based vegetation, color, and spectral indices
from digital images for applications in agriculture, crop
phenotyping, and remote sensing. The methods are based on
digital image processing and plant phenotyping approaches
(Singh et al. (2023) &lt;doi:10.1080/10106049.2022.2160831&gt;).</description><link>https://github.com/r-universe/santosharathod/actions/runs/26680598037</link><pubDate>Wed, 29 Apr 2026 09:30:49 GMT</pubDate><r:package>rgbIndices</r:package><r:version>0.1.1</r:version><r:status>success</r:status><r:repository>https://santosharathod.r-universe.dev</r:repository><r:upstream>https://github.com/cran/rgbIndices</r:upstream><r:article><r:source>rgbIndices.Rmd</r:source><r:filename>rgbIndices.html</r:filename><r:title>RGB Visible Indices for Image Analysis</r:title><r:created>2026-04-29 09:30:49</r:created><r:modified>2026-04-29 09:30:49</r:modified></r:article></item><item><title>[santosharathod] srpi 0.1.0</title><author>santoshagriculture@gmail.com (Santosha Rathod)</author><description>Flexible implementation of the Standardized Ranking
Performance Index (sRPI) for model selection based on multiple
evaluation criteria. The package combines multiple statistical
measures into a single index to provide an objective and robust
ranking of models across calibration, validation, and combined
scenarios. It supports evaluation of statistical, machine
learning, and other predictive models using user-defined
performance criteria. For more details see Aschonitis et al.
(2019) &lt;doi:10.1016/j.envsoft.2019.01.005&gt; and Singh et al.
(2023) &lt;doi:10.1016/j.ecoinf.2022.101933&gt;.</description><link>https://github.com/r-universe/santosharathod/actions/runs/26275261283</link><pubDate>Tue, 21 Apr 2026 21:10:26 GMT</pubDate><r:package>srpi</r:package><r:version>0.1.0</r:version><r:status>success</r:status><r:repository>https://santosharathod.r-universe.dev</r:repository><r:upstream>https://github.com/cran/srpi</r:upstream></item><item><title>[santosharathod] AgriDiversiX 0.1.0</title><author>santoshagriculture@gmail.com (Santosha Rathod)</author><description>Provides functions to compute agricultural crop
diversification indices for crop data across zones and years.
The package implements widely used diversification and
concentration measures including Herfindahl Index,Simpson
Index, Entropy Index, Ogive Index, and Maximum Proportion
Index.</description><link>https://github.com/r-universe/santosharathod/actions/runs/26751467770</link><pubDate>Wed, 01 Apr 2026 11:17:22 GMT</pubDate><r:package>AgriDiversiX</r:package><r:version>0.1.0</r:version><r:status>success</r:status><r:repository>https://santosharathod.r-universe.dev</r:repository><r:upstream>https://github.com/cran/AgriDiversiX</r:upstream></item></channel></rss>