Package: gcf Title: Generalized Covariate Field Version: 0.1.1 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) . License: GPL-3 Encoding: UTF-8 Depends: R (>= 4.1.0) Imports: geocomplexity, ranger, sf, spdep (>= 1.1-7), 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: 2026-10-01 00:15:22 UTC; root Author: Yongze Song [aut, cre, cph] (ORCID: ) Maintainer: Yongze Song Repository: https://cran.r-universe.dev Date/Publication: 2026-09-30 23:59:34 UTC RemoteUrl: https://github.com/cran/gcf RemoteRef: HEAD RemoteSha: a5a96740608765b1e7ed1bd716e21c620ba38fba