58 lines
1.1 KiB
R
58 lines
1.1 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/predict_dim.R
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\name{predict_dim}
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\alias{predict_dim}
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\title{\code{"TODO: @Lukas"}}
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\usage{
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predict_dim(object, ..., method = "CV")
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}
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\arguments{
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\item{object}{instance of class \code{cve} (result of \code{\link{cve}},
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\code{\link{cve.call}}).}
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\item{...}{ignored.}
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\item{method}{one of \code{"CV"}, \code{"elbow"} or \code{"wilcoxon"}.}
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}
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\value{
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list with \code{"k"} the predicted dimension and method dependent
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informatoin.
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}
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\description{
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\code{"TODO: @Lukas"}
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}
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\section{Method cv}{
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TODO: \code{"TODO: @Lukas"}.
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}
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\section{Method elbow}{
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TODO: \code{"TODO: @Lukas"}.
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}
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\section{Method wilcoxon}{
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TODO: \code{"TODO: @Lukas"}.
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}
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\examples{
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# create B for simulation
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B <- rep(1, 5) / sqrt(5)
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set.seed(21)
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# creat predictor data x ~ N(0, I_p)
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x <- matrix(rnorm(500), 100)
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# simulate response variable
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# y = f(B'x) + err
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# with f(x1) = x1 and err ~ N(0, 0.25^2)
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y <- x \%*\% B + 0.25 * rnorm(100)
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# Calculate cve for unknown k between min.dim and max.dim.
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cve.obj.simple <- cve(y ~ x)
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predict_dim(cve.obj.simple)
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}
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