Package: sisireg 1.1.2

Lars Metzner

sisireg: 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").

Authors:Lars Metzner [aut, cre]

sisireg_1.1.2.tar.gz
sisireg_1.1.2.tar.gz(r-4.5-noble)sisireg_1.1.2.tar.gz(r-4.4-noble)
sisireg_1.1.2.tgz(r-4.4-emscripten)sisireg_1.1.2.tgz(r-4.3-emscripten)
sisireg.pdf |sisireg.html
sisireg/json (API)

# Install 'sisireg' in R:
install.packages('sisireg', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 296 downloads 22 exports 13 dependencies

Last updated 2 months agofrom:1f4d69efbf. Checks:2 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 11 2025
R-4.5-linux-x86_64OKFeb 11 2025

Exports:axeaxe_narch_modelaxe_narch_predictfii_modelfii_predictiononnx_loadonnx_savepsplotpsplot3dpsplotndpsvalidrunvalidsnarchssrssr_predictssr3dssr3d_predictssrmlp_predictssrmlp_trainssrndssrnd_predicttauM

Dependencies:herejsonlitelatticeMatrixpngrappdirsRcppRcppTOMLreticulaterlangrprojrootwithrzoo