Package: engression 0.1.4

Nicolai Meinshausen

engression: Engression Modelling

Fits engression models for nonlinear distributional regression. Predictors and targets can be univariate or multivariate. Functionality includes estimation of conditional mean, estimation of conditional quantiles, or sampling from the fitted distribution. Training is done full-batch on CPU (the python version offers GPU-accelerated stochastic gradient descent). Based on "Engression: Extrapolation for nonlinear regression?" by Xinwei Shen and Nicolai Meinshausen (2023). Also supports classification (experimental). <arxiv:2307.00835>.

Authors:Xinwei Shen [aut], Nicolai Meinshausen [aut, cre]

engression_0.1.4.tar.gz
engression_0.1.4.tar.gz(r-4.5-noble)engression_0.1.4.tar.gz(r-4.4-noble)
engression_0.1.4.tgz(r-4.4-emscripten)engression_0.1.4.tgz(r-4.3-emscripten)
engression.pdf |engression.html✨
engression/json (API)

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

Bug tracker:https://github.com/xwshen51/engression/issues

On CRAN:

Conda:

1.00 score 199 downloads 1 exports 25 dependencies

Last updated 1 years agofrom:cdb9e25d1c. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 17 2025
R-4.5-linuxOKMar 17 2025
R-4.4-linuxOKMar 17 2025

Exports:engression

Dependencies:bitbit64callrclicolorspacecorodescfarvergluejsonlitelabelinglifecyclemagrittrmunsellprocessxpsR6RColorBrewerRcpprlangsafetensorsscalestorchviridisLitewithr