SECdistrUv and SECdistrMvPlotting methods for classes SECdistrUv and SECdistrMv
# S4 method for SECdistrUv
plot(x, range, probs, main, npt = 251, ...)# S4 method for SECdistrMv
plot(x, range, probs, npt, landmarks = "auto",
main, comp, compLabs, data = NULL, data.par = NULL, gap = 0.5, ...)
an invisible list. In the univariate case the list has three components:
the input object representing the distribution and two numeric vectors with
the coordinates of the plotted density values.
In the multivariate case, the first element of the list is the input object
representing the distribution and all subsequent list elements are lists with
components of the panels comprising the matrix plot;
the elements of these sub-lists are:
the vectors of x and y coordinates, the names of the variables,
the density values at the (x,y) points, a vector of the density levels
of the curves appearing in each panel plot, with the corresponding approximate
probability content as a vector attribute.
an object of class SECdistrUv or SECdistrMv.
in the univariate case, a vector of length 2 which defines the plotting range; in the multivariate case, a matrix with two rows where each column defines the plotting range of the corresponding component variable. If missing, a sensible choice is made.
a vector of probability values. In the univariate case, the
corresponding quantiles are plotted on the horizontal axis; it can be
skipped by setting probs=NULL. In the multivariate case, each
probability value corresponds to a contour level in each bivariate plot;
at least one probability value is required. See ‘Details’ for
further information. Default value: c(0.05, 0.25, 0.5, 0.75, 0.95)
in the univariate case, c(0.25, 0.5, 0.75, 0.95) in the
multivariate case.
a numeric value or vector (in the univariate and in the
multivariate case, respectively) to assign the number of evaluation points
of the distribution, on an equally-spaced grid over the range
defined above. Default value: 251 in the univariate case, a vector of
101's in the multivariate case.
a character string which affects the placement of some
landmark values in the multivariate case, that is, the origin, the mode
and the mean (or its substitute pseudo-mean), which are all aligned.
Possible values: "proper", "pseudo", "auto"
(default), "". The option "" prevents plotting of the
landmarks. With the other options, the landmarks are plotted, with some
variation in the last one: "proper" plots the proper mean value,
"pseudo" plots the pseudo-mean, useful when the proper mean does
not exists, "auto" plots the proper mean if it exists, otherwise it
switches automatically to the pseudo-mean. See dp2cp for
more information on pseudo-CP parameters, including pseudo-mean.
a character string for main title; if missing, one is built from the available ingredients.
a subset of the vector 1:d, if d denotes the
dimensionality of the multivariate distribution.
a vector of character strings or expressions used to denote
the variables in the plot;
if missing, slot(object,"compNames") is used.
an optional set of data of matching dimensionity of
object to be superimposed to the plot.
The default value data=NULL produces no effect.
In the univariate case, data are plotted using rug
at the top horizontal axis, unless if probs=NULL, in which case
plotting is at the bottom axis. In the multivariate case, points are
plotted in the form of a scatterplot or matrix of scatterplots; this
can be regulated by argument data.par.
an optional list of graphical parameters used for plotting
data in the multivariate case, when data is not NULL.
Recognized parameters are: col, pch, cex.
If missing, the analogous components of par() are used.
a numeric value which regulates the gap between panels of a
multivariate plot when d>2.
additional graphical parameters
Adelchi Azzalini
% \item{\code{signature(x = "ANY", y = "ANY")}}{Generic function: see % \code{\link[graphics]{plot}}.}
signature(x = "SECdistrUv")Plot an object x
of class SECdistrUv.
signature(x = "SECdistrMv")Plot an object x
of class SECdistrMv.
For univariate density plots, probs are used to compute quantiles
from the appropriate distribution, and these are superimposed to the plot of
the density function, unless probs=NULL. In the multivariate case,
each bivariate plot is constructed as a collection of contour curves,
one curve for each probability level; consequently, probs cannot be
missing or NULL. The level of the density contour lines are chosen
so that each curve circumscribes a region with the quoted probability,
to a good degree of approssimation; for additional information, see
Azzalini and Capitanio (2014), specifically Complement 5.2 and p.179,
and references therein.
Azzalini, A. with the collaboration of Capitanio, A. (2014). The Skew-Normal and Related Families. Cambridge University Press, IMS Monographs series.
makeSECdistr, summary.SECdistr,
dp2cp
# d=1
f1 <- makeSECdistr(dp=c(3,2,5), family="SC", name="Univariate Skew-Cauchy")
plot(f1)
plot(f1, range=c(-3,40), probs=NULL, col=4)
#
# d=2
Omega2 <- matrix(c(3, -3, -3, 5), 2, 2)
f2 <- makeSECdistr(dp=list(c(10,30), Omega=Omega2, alpha=c(-3, 5)),
family="sn", name="SN-2d", compNames=c("x1","x2"))
plot(f2)
x2 <- rmsn(100, dp=slot(f2,"dp"))
plot(f2, main="Distribution 'f2'", probs=c(0.5,0.9), cex.main=1.5, col=2,
cex=0.8, compLabs=c(expression(x[1]), expression(log(z[2]-beta^{1/3}))),
data=x2, data.par=list(col=4, cex=0.6, pch=5))
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