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").


Reference manual

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0.9.1 by Lars Metzner, a month ago

Browse source code at

Authors: Lars Metzner [aut, cre]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports zoo, raster

See at CRAN