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'))

Peer review:

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

1.00 score 182 downloads 22 exports 13 dependencies

Last updated 11 days agofrom:1f4d69efbf. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 13 2024
R-4.5-linux-x86_64OKDec 13 2024

Exports:axeaxe_narch_modelaxe_narch_predictfii_modelfii_predictiononnx_loadonnx_savepsplotpsplot3dpsplotndpsvalidrunvalidsnarchssrssr_predictssr3dssr3d_predictssrmlp_predictssrmlp_trainssrndssrnd_predicttauM

Dependencies:herejsonlitelatticeMatrixpngrappdirsRcppRcppTOMLreticulaterlangrprojrootwithrzoo