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message: 'To cite package "SingRegKrig" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'SingRegKrig: Singularity Regression Kriging for Spatial Prediction'
version: 0.1.0
doi: 10.32614/CRAN.package.SingRegKrig
abstract: 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) <https://doi.org/10.1080/15481603.2026.2690341>,
  with singularity theory from Cheng (2012) <https://doi.org/10.1016/j.gexplo.2012.07.007>
  and Cheng (2017) <https://doi.org/10.1016/j.gr.2017.07.011>, random forest methodology
  from Breiman (2001) <https://doi.org/10.1023/A:1010933404324>, and regression kriging
  framework from Hengl, Heuvelink, and Rossiter (2007) <https://doi.org/10.1016/j.cageo.2007.05.001>.
authors:
- family-names: Tyagi
  given-names: Shikhar
  email: shikhar1093tyagi@gmail.com
  orcid: https://orcid.org/0000-0003-1606-0844
- family-names: Pandey
  given-names: Arvind
  email: arvindmzu@gmail.com
- family-names: Singh
  given-names: Bhupendra
  email: bhupendra.rana@gmail.com
- family-names: Tripathi
  given-names: Vrijesh
  email: vrijesh.tripathi@uwi.edu
repository: https://shikhartyagi.r-universe.dev
commit: 3c9b16195ebbb9e4d0c57a34b7aad4962ed7ebc1
date-released: '2026-08-08'
contact:
- family-names: Tyagi
  given-names: Shikhar
  email: shikhar1093tyagi@gmail.com
  orcid: https://orcid.org/0000-0003-1606-0844