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.
Package details |
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Author | Wenying Deng [aut, cre], Jeremiah Zhe Liu [ctb] |
Maintainer | Wenying Deng <wdeng@g.harvard.edu> |
License | GPL-2 |
Version | 0.1-2 |
Package repository | View on CRAN |
Installation |
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