Package: sisireg 1.1.1

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_1.1.1.tar.gz
sisireg_1.1.1.tar.gz(r-4.5-noble)sisireg_1.1.1.tar.gz(r-4.4-noble)
sisireg_1.1.1.tgz(r-4.4-emscripten)sisireg_1.1.1.tgz(r-4.3-emscripten)
sisireg.pdf |sisireg.html✨
sisireg/json (API)

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22 exports 0.00 score 16 dependencies 265 downloads

Last updated 12 months agofrom:f5cc30357b. Checks:OK: 2. Indexed: yes.

Exports:axeaxe_narch_modelaxe_narch_predictfii_modelfii_predictiononnx_loadonnx_savepsplotpsplot3dpsplotndpsvalidrunvalidsnarchssrssr_predictssr3dssr3d_predictssrmlp_predictssrmlp_trainssrndssrnd_predicttauM

Dependencies:herejsonlitelatticeMatrixpngrappdirsrasterRcppRcppTOMLreticulaterlangrprojrootspterrawithrzoo