Package: qqkrls
Type: Package
Title: Quantile-on-Quantile Kernel Regularized Least Squares
Version: 1.0.0
Authors@R: c(
    person("Merwan", "Roudane",
           email = "merwanroudane920@gmail.com",
           role = c("aut", "cre", "cph")),
    person("Tomiwa Sunday", "Adebayo", role = "ctb",
           comment = "Original QQKRLS methodology"),
    person("Jens", "Hainmueller", role = "ctb",
           comment = "Original KRLS methodology"),
    person("Chad", "Hazlett", role = "ctb",
           comment = "Original KRLS methodology"))
Description: Implements Quantile-on-Quantile Kernel-Based Regularized
    Least Squares (QQKRLS) as in Adebayo, Ozkan and Eweade (2024)
    <doi:10.1016/j.jclepro.2024.140832>. Combines Kernel-Based
    Regularized Least Squares (KRLS) of Hainmueller and Hazlett (2014)
    <doi:10.1093/pan/mpt019> with the Quantile-on-Quantile regression
    of Sim and Zhou (2015) <doi:10.1016/j.jbankfin.2015.01.013>: for
    each quantile theta of the independent variable the response is fit
    by KRLS on the corresponding sub-sample and the tau-quantile of the
    resulting pointwise marginal effects yields beta(theta, tau).
    Standard errors come from a paired bootstrap. Visualisations use
    the 'MATLAB' 'Parula' colour map by default.
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.3.1
Depends: R (>= 3.5.0)
Imports: KRLS (>= 1.0-0), plotly (>= 4.0.0), stats, utils, grDevices
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
URL: https://github.com/merwanroudane/qqkrlsr
BugReports: https://github.com/merwanroudane/qqkrlsr/issues
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2026-05-28 12:45:49 UTC; HP
Author: Merwan Roudane [aut, cre, cph],
  Tomiwa Sunday Adebayo [ctb] (Original QQKRLS methodology),
  Jens Hainmueller [ctb] (Original KRLS methodology),
  Chad Hazlett [ctb] (Original KRLS methodology)
Maintainer: Merwan Roudane <merwanroudane920@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-01 09:00:14 UTC
Built: R 4.6.0; ; 2026-06-01 10:29:10 UTC; unix
