Implementation of the CVE (Conditional Variance Estimation) method proposed by Fertl, L. and Bura, E. (2021) <arXiv:2102.08782> and the ECVE (Ensemble Conditional Variance Estimation) method introduced in Fertl, L. and Bura, E. (2021) <arXiv:2102.13435>. CVE and ECVE are sufficient dimension reduction methods in regressions with continuous response and predictors. CVE applies to general additive error regression models while ECVE generalizes to nonadditive error regression models. They operate under the assumption that the predictors can be replaced by a lower dimensional projection without loss of information. It is a semiparametric forward regression model based exhaustive sufficient dimension reduction estimation method that is shown to be consistent under mild assumptions.
Package details 


Author  Daniel Kapla [aut, cph, cre], Lukas Fertl [aut, cph], Efstathia Bura [ctb] 
Maintainer  Daniel Kapla <daniel@kapla.at> 
License  GPL3 
Version  1.1 
URL  https://git.artist.cc/daniel/CVE 
Package repository  View on CRAN 
Installation 
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