scatter {ade4} | R Documentation |
scatter
is a generic function. It has methods for the classes coa
, dudi
, fca
, acm
and pco
.
The scale of the grid is situated on the right-top of the graph.
The points are in the middle of the labels.
This process plots the graphs of the multivariate analyses.
The two axes have the same scale.
scatter(x, ...)
x |
an object used to select a method |
... |
further arguments passed to or from other methods |
The functions scatter use some utilities functions :
Daniel Chessel chessel@biomserv.univ-lyon1.fr
s.arrow
, s.chull
, s.class
,
s.corcircle
, s.distri
, s.label
,
s.match
, s.traject
, s.value
par(mfrow = c(3,3)) plot.new() scatterutil.legendgris(1:20, 4, 1.6) plot.new() scatterutil.sub("lkn5555555555lkn", csub = 2, possub = "bottomleft") scatterutil.sub("lkn5555555555lkn", csub = 1, possub = "topleft") scatterutil.sub("jdjjl", csub = 3, possub = "topright") scatterutil.sub("**", csub = 2, possub = "bottomright") x <- c(0.5,0.2,-0.5,-0.2) ; y <- c(0.2,0.5,-0.2,-0.5) eti <- c("toto", "kjbk", "gdgiglgl", "sdfg") plot(x, y, xlim = c(-1,1), ylim = c(-1,1)) scatterutil.eti.circ(x, y, eti, 2.5) abline(0, 1, lty = 2) ; abline(0, -1, lty = 2) x <- c(0.5,0.2,-0.5,-0.2) ; y <- c(0.2,0.5,-0.2,-0.5) eti <- c("toto", "kjbk", "gdgiglgl", "sdfg") plot(x, y, xlim = c(-1,1), ylim = c(-1,1)) scatterutil.eti(x, y, eti, 1.5) plot(runif(10,-3,5), runif(10,-1,1), asp = 1) scatterutil.grid(2) abline(h = 0, v = 0, lwd = 3) x <- runif(10,0,1) ; y <- rnorm(10) ; z <- rep(1,10) plot(x,y) ; scatterutil.star(x, y, z, 0.5) plot(x,y) ; scatterutil.star(x, y, z, 1) x <- c(runif(10,0,0.5), runif(10,0.5,1)) y <- runif(20) plot(x, y, asp = 1) # asp=1 is essential to have perpendicular axes scatterutil.ellipse(x, y, rep(c(1,0), c(10,10)), cell = 1.5, ax = TRUE) scatterutil.ellipse(x, y, rep(c(0,1), c(10,10)), cell = 1.5, ax = TRUE) x <- c(runif(100,0,0.75), runif(100,0.25,1)) y <- c(runif(100,0,0.75), runif(100,0.25,1)) z <- factor(rep(c(1,2), c(100,100))) plot(x, y, pch = rep(c(1,20), c(100,100))) scatterutil.chull(x, y, z, opt = c(0.25,0.50,0.75,1)) par(mfrow = c(1,1))