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pencopula (version 0.2.1)

plot.pencopula: Plot the estimated copula density or copula distribution.

Description

The function plots the estimated copula density or the copula distrubtion, using the R-package 'lattice'.

Usage

plot.pencopula(x, val = NULL, marg = TRUE, plot = TRUE, int = FALSE,
main.txt = NULL, sub.txt = NULL, contour = FALSE, cond = NULL, cuts =
20, cex = 1, cex.axes = 1, xlab = NULL, ylab = NULL, zlab=NULL,...)

Arguments

x
object of class 'pencopula'.
val
Default val = NULL, one can calculate the estimated density in for p-dimensional vector, e.g. val=c(0.5,1) for the two dimensional case.
marg
Default = TRUE, plotting the marginal densities.
plot
Default = TRUE, if 'FALSE' no plot is shown, e.g. for calculations with val != NULL.
int
Default = FALSE, if TRUE, the integral, i.e. the distribution of the copula density is plotted.
main.txt
Default = NULL shows 'd', 'D', the values of lambda, the penalty order and the degree of the B-splines.
sub.txt
Default = NULL shows the log-likelihood, the penalized log-likelihood and the AIC-value of the estimation.
contour
If TRUE, a contour plot is shown. Default = FALSE.
cond
Default = NULL, if the dimension of data 'p' is higher than 2, one can plot a two-dimensional conditional plot. The user specifies p-2 values for the plot, indicating with '-1'. So for a three-dimensional plot, cond=c(0,-1,-1) shows the de
cuts
Number of cuts for the contour plots, if contour=TRUE.
cex
Default = 1, determing the size of the main of the plot.
cex.axes
Default = 1, determing the size of the labels at the axes.
xlab
Default = NULL and no text is printed at the xlab
ylab
Default = NULL and no text is printed at the ylab
zlab
Default = NULL and 'density' is printed at the zlab for int=FALSE and 'distribution' for int=TRUE.
...
further arguments

Value

  • If 'val' is not NULL, the function returns a matrix with the calculated density or distribution values for the set 'val'.

Details

For the two dimensional plots, a equidistant grid of 21 values between 0 and 1 is constructed. The plot consists of the density or distribution values in this grid points. For plots of high dimensional data (p>2), one has to fix p-2 covariates (see 'cond').

References

Flexible Copula Density Estimation with Penalized Hierarchical B-Splines, Kauermann G., Schellhase C. and Ruppert, D. (2011), to appear.