| plot.pencopula {pencopulaCond} | R Documentation |
Plot the estimated copula density or copula distribution.
Description
The function plots the estimated copula density or the copula distrubtion for a paircopula, using the R-package 'lattice'.
Usage
## S3 method for class 'pencopula'
plot(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, cex.contour=1, xlab = NULL, ylab = NULL,
zlab=NULL, zlim=NULL, biv.margin=NULL, show.observ=FALSE,cond.cop=FALSE,
cond.par,margin.normal=FALSE,...)
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 density/distribution ith fixed first covariate and the second and third covariates vary. |
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. |
cex.contour |
Default = 1, determing the size of the labels at the cuts of the contourplot. |
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. |
zlim |
For Default = NULL, the range of the estimated values determin zlim. Alternatively, one can suggest the range as a vector. |
biv.margin |
Determines for which parameter the bivariate marginal distribution/density is presented. |
show.observ |
Default = FALSE. If TRUE, plotting the original observation into a contourplot. For multivariate copulas the data corresponding to 'biv.margin' is plotted. Show.observ is not possible in combination with option 'cond'. |
cond.cop |
Default=FALSE. If cond.cop=TRUE, the object x have to be condtional copula - this option will disapper as the object itself contains this information. |
cond.par |
If cond.cop=TRUE, the plot is created for the conditioning argument cond.par |
margin.normal |
Default = FALSE. If TRUE, the plot is presented with margins following standard normal distribution. |
... |
further arguments |
Details
For the two dimensional plots, a equidistant grid of 51 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').
Value
If 'val' is not NULL, the function returns a matrix with the calculated density or distribution values for the set 'val'.
Author(s)
Christian Schellhase <cschellhase@wiwi.uni-bielefeld.de>
References
Estimating Non-Simplified Vine Copulas Using Penalized Splines, Schellhase, C. and Spanhel, F. (2017), Statistics and Computing.