ade4 (version 1.01)

kplot.sepan: Multiple Graphs for Separed Analyses in a K-tables

Description

performs high level plots for Separed Analyses in a K-tables, using an object of class sepan.

Usage

kplot.sepan(object, xax = 1, yax = 2, which.tab = 1:length(sep$blo), 
    mfrow = NULL, permute.row.col = FALSE, clab.row = 1, 
    clab.col = 1.25, traject.row = FALSE, csub = 2, 
    possub = "bottomright", show.eigen.value = TRUE,...)
kplot.sepan.coa (object, xax = 1, yax = 2, which.tab = 1:length(sep$blo), 
    mfrow = NULL, permute.row.col = FALSE, clab.row = 1, 
    clab.col = 1.25, csub = 2, possub = "bottomright", 
    show.eigen.value = TRUE, poseig = c("bottom", "top"), ...)

Arguments

object

an object of class sepan

xax, yax

the numbers of the x-axis and the y-axis

which.tab

a numeric vector containing the numbers of the tables to analyse

mfrow

parameter for the array of figures to be drawn, otherwise use n2mfrow

permute.row.col

if TRUE the rows are represented by arrows and the columns by points, if FALSE it is the opposite

clab.row

a character size for the row labels

clab.col

a character size for the column labels

traject.row

a logical value indicating whether the trajectories between rows should be drawn in a natural order

csub

a character size for the sub-titles, used with par("cex")*csub

possub

a string of characters indicating the sub-title position ("topleft","topright","bottomleft","bottomright")

show.eigen.value

a logical value indicating whether the eigenvalues bar plot should be drawn

poseig

if "top" the eigenvalues bar plot is upside, if "bottom", it is downside

...

further arguments passed to or from other methods

Details

kplot.sepan superimposes the points for the rows and the arrows for the columns using an adapted rescaling such as the scatter.dudi. kplot.sepan.coa superimposes the row coordinates and the column coordinates with the same scale.

Examples

data(escopage)
w <- data.frame(scale(escopage$tab))
w <- ktab.data.frame(w, escopage$blo, tabnames = escopage$tab.names)
sep1 <- sepan(w)
kplot(sep1, show = FALSE)

data(friday87)
w <- data.frame(scale(friday87$fau, scal = FALSE))
w <- ktab.data.frame(w, friday87$fau.blo, tabnames = friday87$tab.names)
kplot(sepan(w), clab.r = 1.25, clab.c = 0, csub = 3)

data(microsatt)
w <- dudi.coa(data.frame(t(microsatt$tab)), scann = FALSE)
loci.fac <- factor(rep(microsatt$loci.names, microsatt$loci.eff))
wit <- within(w, loci.fac, scann = FALSE)
microsatt.ktab <- ktab.within(wit)
kplot.sepan.coa(sepan(microsatt.ktab), show = FALSE, clab.c = 0, 
    mfrow = c(3,3), clab.r = 1.5)