From 9d0f551dc3869596d4b2ecadb2a041bc40e835c5 Mon Sep 17 00:00:00 2001 From: daniel Date: Tue, 9 Mar 2021 19:24:32 +0100 Subject: [PATCH] final CRAN re-submition (1.0 -> 1.1) changes in DESCRIPTION --- CVarE/DESCRIPTION | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/CVarE/DESCRIPTION b/CVarE/DESCRIPTION index 8ce06c5..0f11c23 100644 --- a/CVarE/DESCRIPTION +++ b/CVarE/DESCRIPTION @@ -12,10 +12,11 @@ Authors@R: c( person("Lukas", "Fertl", role = c("aut", "cph")), person("Efstathia", "Bura", role = "ctb") ) -Description: Implementation of the Conditional Variance Estimation (CVE) method - from Fertl and Bura (2021) and the Ensemble Conditional - Variance Estimation (ECVE) method from Fertl and Bura (2021) . - CVE and ECVE are Sufficient Dimension Reduction (SDR) methods +Description: Implementation of the CVE (Conditional Variance Estimation) method + proposed by Fertl, L. and Bura, E. (2021) and the ECVE + (Ensemble Conditional Variance Estimation) method introduced in + Fertl, L. and Bura, E. (2021) . + 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 non-additive error regression models. They operate under the assumption that the predictors can