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:
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.
Last updated 11 days agofrom:1f4d69efbf. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 13 2024 |
R-4.5-linux-x86_64 | OK | Dec 13 2024 |
Exports:axeaxe_narch_modelaxe_narch_predictfii_modelfii_predictiononnx_loadonnx_savepsplotpsplot3dpsplotndpsvalidrunvalidsnarchssrssr_predictssr3dssr3d_predictssrmlp_predictssrmlp_trainssrndssrnd_predicttauM
Dependencies:herejsonlitelatticeMatrixpngrappdirsRcppRcppTOMLreticulaterlangrprojrootwithrzoo