Sign-Simplicity-Regression-Solver

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").


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install.packages("sisireg")

0.9.1 by Lars Metzner, a month ago


Browse source code at https://github.com/cran/sisireg


Authors: Lars Metzner [aut, cre]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports zoo, raster


See at CRAN