48 lines
		
	
	
		
			1.3 KiB
		
	
	
	
		
			R
		
	
	
	
	
	
			
		
		
	
	
			48 lines
		
	
	
		
			1.3 KiB
		
	
	
	
		
			R
		
	
	
	
	
	
| % Generated by roxygen2: do not edit by hand
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| % Please edit documentation in R/estimateBandwidth.R
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| \name{estimate.bandwidth}
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| \alias{estimate.bandwidth}
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| \title{Bandwidth estimation for CVE.}
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| \usage{
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| estimate.bandwidth(X, k, nObs)
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| }
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| \arguments{
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| \item{X}{data matrix with samples in its rows.}
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| 
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| \item{k}{Dimension of lower dimensional projection.}
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| 
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| \item{nObs}{number of points in a slice, see \eqn{nObs} in CVE paper.}
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| }
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| \value{
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| Estimated bandwidth \code{h}.
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| }
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| \description{
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| Estimates a bandwidth \code{h} according
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| \deqn{%
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| h = (2 * tr(\Sigma) / p) * (1.2 * n^{-1 / (4 + k)})^2}{%
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| h = (2 * tr(\Sigma) / p) * (1.2 * n^(\frac{-1}{4 + k}))^2}
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| with \eqn{n} the sample size, \eqn{p} its dimension
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| (\code{n <- nrow(X); p <- ncol(X)}) and the covariance-matrix \eqn{\Sigma}
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| which is \code{(n-1)/n} times the sample covariance estimate.
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| }
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| \examples{
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| # set dimensions for simulation model
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| p <- 5; k <- 1
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| # create B for simulation
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| B <- rep(1, p) / sqrt(p)
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| # samplsize
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| n <- 100
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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(n * p), n, p)
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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 with method 'simple' for k = 1
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| set.seed(21)
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| cve.obj.simple <- cve(y ~ x, k = k)
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| print(cve.obj.simple$res$'1'$h)
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| print(estimate.bandwidth(x, k = k))
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| }
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