# 1-D plot of a numeric score by means/standard deviations computed using an external table of weights This function represents a set of distributions on a numeric score using a mean-standard deviation display ```r s1d.distri(score, dfdistri, labels = colnames(dfdistri), at = 1:NCOL(dfdistri), yrank = TRUE, sdSize = 1, facets = NULL, plot = TRUE, storeData = TRUE, add = FALSE, pos = -1, ...) ``` ## Arguments - `score`: a numeric vector (or a data frame) used to produce the plot - `dfdistri`: a data frame containing the mass distribution in which each column is a class - `yrank`: a logical to draw the distributions sorted by means ascending order - `labels`: the labels' names drawn for each distribution - `at`: a numeric vector used as an index - `sdSize`: a numeric for the size of the standard deviation segments - `facets`: a factor splitting `score` so that subsets of the data are represented on different sub-graphics - `plot`: a logical indicating if the graphics is displayed - `storeData`: a logical indicating if the data are stored in the returned object. If `FALSE`, only the names of the data arguments are stored - `add`: a logical. If `TRUE`, the graphic is superposed to the graphics already plotted in the current device - `pos`: an integer indicating the position of the environment where the data are stored, relative to the environment where the function is called. Useful only if `storeData` is `FALSE` - ``...``: additional graphical parameters (see `adegpar` and `trellis.par.get`) ## Details Graphical parameters for rugs are available in `plines` of `adegpar`. Some appropriated graphical parameters in `p1d` are also available. The weighted means and standard deviations of class are available in the object slot `stats` using `object@stats$means` and `object@stats$sds`. ## Returns An object of class `ADEg` (subclass `S1.distri`) or `ADEgS` (if `add` is `TRUE` and/or if facets or data frame for `score` are used). The result is displayed if `plot` is `TRUE`. ## Author(s) Alice Julien-Laferriere, Aurelie Siberchicot aurelie.siberchicot@univ-lyon1.fr and Stephane Dray ## See Also `S1.distri` `ADEg.S1` ## Examples ```r w <- seq(-1, 1, le = 200) distri <- data.frame(lapply(1:50, function(x) sample(200:1) * ((w >= (- x / 50)) & (w <= x / 50)))) names(distri) <- paste("w", 1:50, sep = "") g11 <- s1d.distri(w, distri, yrank = TRUE, sdS = 1.5, plot = FALSE) g12 <- s1d.distri(w, distri, yrank = FALSE, sdS = 1.5, plot = FALSE) G1 <- ADEgS(c(g11, g12), layout = c(1, 2)) data(rpjdl, package = "ade4") coa1 <- ade4::dudi.coa(rpjdl$fau, scannf = FALSE) G2 <- s1d.distri(coa1$li[,1], rpjdl$fau, labels = rpjdl$frlab, plabels = list(cex = 0.8, boxes = list(draw = FALSE))) ## Not run: g31 <- s1d.distri(coa1$l1[,1], rpjdl$fau, plabels = list(cex = 0.8, boxes = list(draw = FALSE)), plot = FALSE) nsc1 <- ade4::dudi.nsc(rpjdl$fau, scannf = FALSE) g32 <- s1d.distri(nsc1$l1[,1], rpjdl$fau, plabels = list(cex = 0.8, boxes = list(draw = FALSE)), plot = FALSE) g33 <- s.label(coa1$l1, plot = FALSE) g34 <- s.label(nsc1$l1, plot = FALSE) G3 <- ADEgS(c(g31, g32, g33, g34), layout = c(2, 2)) ## End(Not run) ```

s1d.distri function