Package: sisireg 1.2.1

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_1.2.1.tar.gz
sisireg_1.2.1.tar.gz(r-4.7-arm64)sisireg_1.2.1.tar.gz(r-4.7-x86_64)sisireg_1.2.1.tar.gz(r-4.6-arm64)sisireg_1.2.1.tar.gz(r-4.6-x86_64)
sisireg_1.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
sisireg/json (API)

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

On CRAN:

Conda:

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

1.00 score 173 downloads 27 exports 13 dependencies

Last updated from:2b039f6e27. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK122
linux-devel-x86_64OK137
source / vignettesOK153
linux-release-arm64OK144
linux-release-x86_64OK119
wasm-releaseOK100

Exports:axeaxe_narch_modelaxe_narch_predictfii_modelfii_predictiononnx_loadonnx_savepsplotpsplot3dpsplotndpsplotnd2psvalidrunvalidsnarchssrssr_predictssr3dssr3d_predictssrmlp_predictssrmlp_trainssrmlp2_trainssrndssrnd_predictssrnd2ssrnd2_predictssrnd2NNtauM

Dependencies:herejsonlitelatticeMatrixpngrappdirsRcppRcppTOMLreticulaterlangrprojrootwithrzoo