sco.distri {ade4} | R Documentation

## Representation by mean- standard deviation of a set of weight distributions on a numeric score

### Description

represents the mean- standard deviation of a set of weight distributions on a numeric score.

### Usage

    sco.distri(score, df, y.rank = TRUE, csize = 1, labels = names(df), clabel = 1,
        xlim = NULL, grid = TRUE, cgrid = 0.75,
        include.origin = TRUE, origin = 0, sub = NULL, csub = 1)

### Arguments

`score` | a numeric vector
`df` | a data frame with only positive or null values
`y.rank` | a logical value indicating whether the means should be classified in ascending order
`csize` | an integer indicating the size segment
`labels` | a vector of strings of characters for the labels of the variables
`clabel` | if not NULL, a character size for the labels, used with `par("cex")*clabel`
`xlim` | the ranges to be encompassed by the x axis, if NULL they are computed
`grid` | a logical value indicating whether the scale vertical lines should be drawn
`cgrid` | a character size, parameter used with `par("cex")*cgrid` to indicate the mesh of the scale
`include.origin` | a logical value indicating whether the point "origin" should be belonged to the graph space
`origin` | the fixed point in the graph space, for example c(0,0) the origin axes
`sub` | a string of characters to be inserted as legend
`csub` | a character size for the legend, used with `par("cex")*csub`

### Examples

    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 = "")
    par(mfrow = c(1,2))
    sco.distri(w, distri, csi = 1.5)
    sco.distri(w, distri, y.rank = FALSE, csi = 1.5)
    par(mfrow = c(1,1))

    data(rpjdl)
    coa2 <- dudi.coa(rpjdl$fau, FALSE)
    sco.distri(coa2$li[,1], rpjdl$fau, lab = rpjdl$frlab, clab = 0.8)

    data(doubs)
    par(mfrow = c(2,2))
    poi.coa <- dudi.coa(doubs$poi, scann = FALSE)
    sco.distri(poi.coa$l1[,1], doubs$poi)
    poi.nsc <- dudi.nsc(doubs$poi, scann = FALSE)
    sco.distri(poi.nsc$l1[,1], doubs$poi)
    s.label(poi.coa$l1)
    s.label(poi.nsc$l1)

    data(rpjdl)
    fau.coa <- dudi.coa(rpjdl$fau, scann = FALSE)
    sco.distri(fau.coa$l1[,1], rpjdl$fau)
    fau.nsc <- dudi.nsc(rpjdl$fau, scann = FALSE)
    sco.distri(fau.nsc$l1[,1], rpjdl$fau)
    s.label(fau.coa$l1)
    s.label(fau.nsc$l1)

    par(mfrow = c(1,1))

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