gcf: Generalized Covariate Field
Generates generalized covariate field (GCF) variables from
spatial covariates observed at projected coordinates, and selects a
stable subset of them for geospatial prediction. For each input
covariate the method builds spatial-pattern features (local indicator
of spatial association, local Geary's c, log local variance, rank
quantile entropy, geocomplexity, log scale variance, local variogram
exponent, and signed z-score and median absolute deviation outlier
strengths over a series of buffer radii) and neighbourhood-distribution
features (buffer-wise quantiles of the covariate values surrounding
each location), reduces the buffer and quantile sweeps to a compact set
of interpretable functional summaries, and selects variables by random
forest importance combined with spatial-block stability resampling and
group voting. The GCF method is positioned as prediction-oriented
feature construction: its output feeds any downstream regression
learner. Methods are described in Song (2026)
<doi:10.1080/13658816.2026.2729719>.
| Version: |
0.1.0 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
geocomplexity, ranger, sf, spdep, stats, utils |
| Suggests: |
knitr, randomForest, rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2026-09-26 |
| DOI: |
10.32614/CRAN.package.gcf (may not be active yet) |
| Author: |
Yongze Song  [aut,
cre, cph] |
| Maintainer: |
Yongze Song <yongze.song at outlook.com> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| Citation: |
gcf citation info |
| Materials: |
NEWS |
| CRAN checks: |
gcf results |
Documentation:
Downloads:
| Package source: |
gcf_0.1.0.tar.gz |
| Windows binaries: |
r-devel: not available, r-release: not available, r-oldrel: not available |
| macOS binaries: |
r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available |
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