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final CRAN re-submition (1.0 -> 1.1) changes in DESCRIPTION

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Daniel Kapla 2021-03-09 19:24:32 +01:00
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CVarE/DESCRIPTION
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@ -12,10 +12,11 @@ Authors@R: c(
person("Lukas", "Fertl", role = c("aut", "cph")), person("Lukas", "Fertl", role = c("aut", "cph")),
person("Efstathia", "Bura", role = "ctb") person("Efstathia", "Bura", role = "ctb")
) )
Description: Implementation of the Conditional Variance Estimation (CVE) method Description: Implementation of the CVE (Conditional Variance Estimation) method
from Fertl and Bura (2021) <arXiv:2102.08782> and the Ensemble Conditional proposed by Fertl, L. and Bura, E. (2021) <arXiv:2102.08782> and the ECVE
Variance Estimation (ECVE) method from Fertl and Bura (2021) <arXiv:2102.13435>. (Ensemble Conditional Variance Estimation) method introduced in
CVE and ECVE are Sufficient Dimension Reduction (SDR) methods 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 in regressions with continuous response and predictors. CVE applies to general
additive error regression models while ECVE generalizes to non-additive error additive error regression models while ECVE generalizes to non-additive error
regression models. They operate under the assumption that the predictors can regression models. They operate under the assumption that the predictors can