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) and
Wenying et al. (2018) ). 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.