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SingRegKrig

0.1.0

Singularity Regression Kriging for Spatial Prediction

0packages depend
39downloads / year
68.8%test coverage
8/8checks pass

Overview

About
Maintained by Shikhar TyagiFirst published 2026-08-081 releasesCRAN page ↗

Implements the Singularity Regression Kriging ('SRK') model for spatial prediction by integrating covariate singularity feature construction, nonlinear trend estimation via random forest, and geostatistical interpolation of residuals using ordinary kriging. Singularity-based anomaly indices are computed from environmental covariates at multiple spatial scales to capture local multiscale heterogeneity and augment the random forest feature set for trend estimation. The resulting residuals are interpolated using ordinary kriging to generate final spatial predictions with uncertainty quantification. Tools for spatial block cross-validation, parameter sensitivity analysis, and diagnostic visualization are also provided. Methods are based on Ren, Song, Chen, and Yu (2026) doi:10.1080/15481603.2026.2690341, with singularity theory from Cheng (2012) doi:10.1016/j.gexplo.2012.07.007 and Cheng (2017) doi:10.1016/j.gr.2017.07.011, random forest methodology from Breiman (2001) doi:10.1023/A:1010933404324, and regression kriging framework from Hengl, Heuvelink, and Rossiter (2007) doi:10.1016/j.cageo.2007.05.001.

Install

Health

CRAN checks
8OK
Slowest check: 1.2 min · r-oldrel-windows-x86_64
Code health
Yes
Tests · ratio 0.16
68.8%
Coverage · measured lines
100%
Documentation · exports
6
Dependencies · direct
Check history
  • OK2026-08-09
    6 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMENoVignettesNopkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
80%
Documented parameters
100%
Return-value docs
100%
References docs
47%

Downloads

39
CRAN downloads in the past year
Rank #24,870 · ~0/day · ~3/mo
SingRegKrig
Daily download trend is not available in this view yet.

Dependencies

Declared dependencies
4 external dependencies (excludes base and recommended)
Depends (1)
R >= 4.0.0
Imports (6)
statsgraphicsgrDevicesrandomForestgstatsp
LinkingTo (0)
none
Suggests (1)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

Datasets

People & History

People (4)
Maintainer (1)
Author, Maintainer
Authors (4)
Author, Maintainer
Package Timeline

1 release. R releases are shown for context.

  • 0.1.0Latest
    2026-08-08 · current release
  • R
    R 4.6.0 released · 2026-04-24

Package metadata

First published
2026-08-08
Total releases
1 / 1 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 4.0.0
Bundled data
6.0 KB / 1 file
Download size
not tracked yet
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("SingRegKrig")
Tyagi, S., Pandey, A., Singh, B., & Tripathi, V. (2026). SingRegKrig: Singularity Regression Kriging for Spatial Prediction (Version 0.1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.SingRegKrig

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for SingRegKrig version 0.1.0 [Data set]. HJJB, LLC. Data release v2026-08-11. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-11, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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