Package: gcf
Title: Generalized Covariate Field
Version: 0.1.0
Authors@R: 
    person(given = "Yongze", family = "Song",
           email = "yongze.song@outlook.com",
           role = c("aut", "cre", "cph"),
           comment = c(ORCID = "0000-0003-3420-9622"))
Description: 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>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: geocomplexity, ranger, sf, spdep, stats, utils
Suggests: knitr, randomForest, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
LazyData: true
LazyDataCompression: xz
Config/roxygen2/version: 8.1.0
NeedsCompilation: no
Packaged: 2026-09-15 07:02:05 UTC; 268222h
Author: Yongze Song [aut, cre, cph] (ORCID:
    <https://orcid.org/0000-0003-3420-9622>)
Maintainer: Yongze Song <yongze.song@outlook.com>
Repository: CRAN
Date/Publication: 2026-09-26 16:10:02 UTC
