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.
|Author||Wenying Deng [aut, cre], Jeremiah Zhe Liu [ctb]|
|Maintainer||Wenying Deng <firstname.lastname@example.org>|
|Package repository||View on CRAN|
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