Package: sisireg
Title: Sign-Simplicity-Regression-Solver
Version: 1.2.1
Authors@R: 
    person(given = "Lars",
           family = "Metzner",
           role = c("aut", "cre"),
           email = "lars.metzner@ppi.de")
Description: Implementation of the SSR-Algorithm. The Sign-Simplicity-Regression model is a nonparametric statistical model which is based on residual signs and simplicity assumptions on the regression function. Goal is to calculate the most parsimonious regression function satisfying the statistical adequacy requirements. Theory and functions are specified in Metzner (2020, ISBN: 979-8-68239-420-3, "Trendbasierte Prognostik") and Metzner (2021, ISBN: 979-8-59347-027-0, "Adäquates Maschinelles Lernen").
License: GPL (>= 2)
Encoding: UTF-8
Imports: zoo, reticulate
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2025-07-09 08:50:16 UTC; lme
Author: Lars Metzner [aut, cre]
Maintainer: Lars Metzner <lars.metzner@ppi.de>
Repository: CRAN
Date/Publication: 2025-07-09 09:30:02 UTC
Built: R 4.6.0; x86_64-apple-darwin20; 2026-04-27 20:16:54 UTC; unix
Archs: sisireg.so.dSYM
