| plotellipse {SensoMineR} | R Documentation |
Plot confidence ellipses.
plotellipse(mat, alpha = 0.05, coord = c(1,2), eig, cex = 1, color = NULL)
mat |
Matrix with all the points |
alpha |
the confidence level of the ellipses |
coord |
a length 2 vector specifying the components to plot |
eig |
a matrix with the component of the factor analysis (in row) and the eigenvalues, the inertia and the cumulative inertia for each component. Typically, the eig output of the construct.axes function |
cex |
cf. function par in the graphics package |
color |
a vector with the colors used; by default there are 35 colors defined |
François Husson
data(chocolates)
ktab.donnee <- ktab.data.frame(cbind.data.frame(chocolates[,1],
chocolates[,4], chocolates[,-(1:4)]), blocks = c(2,14),
tabnames = c("JP","Gr1"))
ktab.interesting.desc <- search.desc.ktab(ktab.donnee, level = 0.5)
axe <- construct.axes(ktab.interesting.desc, scale.unit = TRUE)
simul <- simulation(axe, nbbloc = length(ktab.interesting.desc$blo)-1)
plotellipse (simul, alpha = 0.05, eig = axe$eig)
#######################################
ktab.donnee <- ktab.data.frame(cbind.data.frame(chocolates[,1],
chocolates[,4],chocolates[,-(1:4)]), blocks = c(2,6,4,4),
tabnames = c("JP","A","F","T"))
ktab.interesting.desc <- search.desc.ktab(ktab.donnee, level = 0.5)
axe <- construct.axes(ktab.interesting.desc, scale.unit = TRUE)
simul <- simulation(axe, nbbloc = length(ktab.interesting.desc$blo)-1)
plotellipse (simul, alpha = 0.05, eig = axe$eig)