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71 lines
1.8 KiB
R
71 lines
1.8 KiB
R
#' Easy function for splitting numeric variable in quantiles
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#'
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#' Using base/stats functions cut() and quantile().
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#'
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#' @param x Variable to cut.
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#' @param groups Number of groups.
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#' @param y alternative vector to draw quantile cuts from. Limits has
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#' to be within x. Default is NULL.
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#' @param na.rm Remove NA's. Default is TRUE.
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#' @param group.names Names of groups to split to. Default is NULL,
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#' giving intervals as names.
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#' @param ordered.f Set resulting vector as ordered. Default is FALSE.
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#' @param detail.list flag to include details or not
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#' @param inc.outs Flag to include min(x) and max(x)
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#' as borders in case of y!=NULL.
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#'
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#' @return vector or list with vector and details (length 2)
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#'
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#' @keywords quantile
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#' @export
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#' @examples
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#' aa <- as.numeric(sample(1:1000,2000,replace = TRUE))
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#' x <- 1:450
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#' y <- 6:750
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#' summary(quantile_cut(aa,groups=4,detail.list=FALSE)) ## Cuts quartiles
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quantile_cut <- function (x,
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groups,
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y = NULL,
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na.rm = TRUE,
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group.names = NULL,
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ordered.f = FALSE,
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inc.outs = FALSE,
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detail.list = FALSE) {
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if (!is.null(y)) {
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q <- quantile(
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y,
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probs = seq(0, 1, 1 / groups),
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na.rm = na.rm,
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names = TRUE,
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type = 7
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)
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if (inc.outs) {
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# Setting cut borders to include outliers in x compared to y.
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q[1] <- min(x, na.rm = TRUE)
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q[length(q)] <- max(x, na.rm = TRUE)
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}
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}
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if (is.null(y)) {
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q <- quantile(
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x,
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probs = seq(0, 1, 1 / groups),
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na.rm = na.rm,
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names = TRUE,
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type = 7
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)
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}
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d <- cut(
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x,
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q,
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include.lowest = TRUE,
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labels = group.names,
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ordered_result = ordered.f
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)
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if (detail.list)
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list(d, q)
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else
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d
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}
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