33 lines
1008 B
R
33 lines
1008 B
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/CVE.R
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\name{cve}
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\alias{cve}
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\title{Conditional Variance Estimator}
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\usage{
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cve(X, Y, k, nObs = sqrt(nrow(X)), tauInitial = 1, tol = 0.001,
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slack = -1e-10, maxIter = 50L, attempts = 10L)
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}
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\arguments{
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\item{X}{A matrix of type numeric of dimensions N times dim where N is the number
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of entries with dim as data dimension.}
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\item{Y}{A vector of type numeric of length N (coresponds to \code{x}).}
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\item{k}{Guess for rank(B).}
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\item{nObs}{As describet in the paper.}
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\item{tol}{Tolerance for optimization stopping creteria.}
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}
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\description{
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Conditional Variance Estimator (CVE) is a novel sufficient dimension
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reduction (SDR) method for regressions satisfying E(Y|X) = E(Y|B'X),
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where B'X is a lower dimensional projection of the predictors.
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}
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\references{
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Fertl Likas, Bura Efstathia. Conditional Variance Estimation for Sufficient Dimension Reduction, 2019
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}
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\seealso{
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TODO: \code{vignette("CVE_paper", package="CVE")}.
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}
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