adegraphics (version 1.0-21)

s1d.distri: 1-D plot of a numeric score by means/standard deviations computed using an external table of weights

Description

This function represents a set of distributions on a numeric score using a mean-standard deviation display

Usage

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, ...)

Value

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.

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)

Author

Alice Julien-Laferriere, Aurelie Siberchicot and Stephane Dray

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.

See Also

S1.distri ADEg.S1

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 = "")
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)))

if (FALSE) {
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))
}