The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
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").
Version: | 1.1.1 |
Imports: | zoo, raster, reticulate |
Published: | 2023-09-20 |
DOI: | 10.32614/CRAN.package.sisireg |
Author: | Lars Metzner [aut, cre] |
Maintainer: | Lars Metzner <lars.metzner at ppi.de> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | yes |
CRAN checks: | sisireg results |
Reference manual: | sisireg.pdf |
Package source: | sisireg_1.1.1.tar.gz |
Windows binaries: | r-devel: sisireg_1.1.1.zip, r-release: sisireg_1.1.1.zip, r-oldrel: sisireg_1.1.1.zip |
macOS binaries: | r-release (arm64): sisireg_1.1.1.tgz, r-oldrel (arm64): sisireg_1.1.1.tgz, r-release (x86_64): sisireg_1.1.1.tgz, r-oldrel (x86_64): sisireg_1.1.1.tgz |
Old sources: | sisireg archive |
Please use the canonical form https://CRAN.R-project.org/package=sisireg to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.