Package: KRLS
Type: Package
Title: Kernel-Based Regularized Least Squares
Version: 1.7-0
Date: 2026-06-04
Authors@R: c(
    person("Jens", "Hainmueller", email = "jhain@stanford.edu", role = c("aut", "cre")),
    person("Chad", "Hazlett", role = "aut"))
Description: Implements Kernel-based Regularized Least Squares (KRLS), a
    machine learning method to fit multidimensional functions y = f(x) for
    regression and classification problems without relying on linearity or
    additivity assumptions. KRLS finds the best fitting function by
    minimizing the squared loss of a Tikhonov regularization problem,
    using Gaussian kernels as radial basis functions. For further details
    see Hainmueller and Hazlett (2014, <doi:10.1093/pan/mpt019>).
License: GPL (>= 2)
Imports: grDevices, graphics, stats
Suggests: lattice, testthat (>= 3.0.0), knitr, rmarkdown, ggplot2,
        generics
Config/testthat/edition: 3
VignetteBuilder: knitr
URL: https://web.stanford.edu/~jhain/, https://github.com/j-hai/KRLS
BugReports: https://github.com/j-hai/KRLS/issues
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-06-05 04:53:37 UTC; jhainmueller
Author: Jens Hainmueller [aut, cre],
  Chad Hazlett [aut]
Maintainer: Jens Hainmueller <jhain@stanford.edu>
Repository: CRAN
Date/Publication: 2026-06-05 07:30:14 UTC
Built: R 4.6.0; ; 2026-06-05 10:58:51 UTC; unix
