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
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, ...)
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 |
plot |
a logical indicating if the graphics is displayed |
storeData |
a logical indicating if the data are stored in
the returned object. If |
add |
a logical. If |
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 |
... |
additional graphical parameters (see
|
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.
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.
Alice Julien-Laferriere, Aurelie Siberchicot aurelie.siberchicot@univ-lyon1.fr and Stephane Dray
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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.