CVEK: Cross-Validated Kernel Ensemble

Implementation of Cross-Validated Kernel Ensemble (CVEK), a flexible modeling framework for robust nonlinear regression and hypothesis testing based on ensemble learning with kernel-ridge estimators (Jeremiah et al. (2017) <arXiv:1710.01406> and Wenying et al. (2018) <arXiv:1811.11025>). It allows user to conduct nonlinear regression with minimal assumption on the function form by aggregating nonlinear models generated from a diverse collection of kernel families. It also provides utilities to test for the estimated nonlinear effect under this ensemble estimator, using either the asymptotic or the bootstrap version of a generalized score test.

Version: 0.1-2
Depends: R (≥ 3.6.0), MASS, limSolve
Suggests: testthat, knitr, rmarkdown, ggplot2, ggrepel
Published: 2020-12-18
Author: Wenying Deng [aut, cre], Jeremiah Zhe Liu [ctb]
Maintainer: Wenying Deng <wdeng at g.harvard.edu>
License: GPL-2
NeedsCompilation: no
CRAN checks: CVEK results

Downloads:

Reference manual: CVEK.pdf
Vignettes: Using the CVEK R package
Package source: CVEK_0.1-2.tar.gz
Windows binaries: r-devel: CVEK_0.1-2.zip, r-release: CVEK_0.1-2.zip, r-oldrel: CVEK_0.1-2.zip
macOS binaries: r-release: CVEK_0.1-2.tgz, r-oldrel: CVEK_0.1-2.tgz
Old sources: CVEK archive

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