52 lines
1.3 KiB
R
52 lines
1.3 KiB
R
#' Prints a summary of a \code{cve} result.
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#' @param object Instance of 'cve' as returned by \code{cve}.
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#' @param ... ignored.
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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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#'
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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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#'
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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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#'
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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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#'
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#' summary(cve.obj.simple)
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#'
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#' @method summary cve
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#' @export
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summary.cve <- function(object, ...) {
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cat('Summary of CVE result - Method: "', object$method, '"\n',
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'\n',
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'Dataset size: ', nrow(object$X), '\n',
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'Data Dimension: ', ncol(object$X), '\n',
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# 'SDR Dimension: ', object$k, '\n',
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# 'loss: ', object$loss, '\n',
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'\n',
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'Called via:\n',
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' ',
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sep='')
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print(object$call)
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L <- c()
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k <- c()
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for (dr.k in object$res) {
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if (class(dr.k) == 'cve.k') {
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k <- c(k, as.character(dr.k$k))
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L <- c(L, dr.k$L)
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}
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}
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L <- matrix(L, ncol = length(k))
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S <- apply(L, 2, summary)
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colnames(S) <- k
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cat('\n')
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print(S)
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}
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