# plot.paircopula: Flexible Pair-Copula Estimation in D-vines with Penalized... In penRvine: Flexible R-Vines Estimation Using Bivariate Penalized Splines

## Description

Plotting a paircopula of class 'paircopula'.

## Usage

 ```1 2 3 4 5``` ```## S3 method for class 'paircopula' plot(x,val=NULL,marg=TRUE,plot=TRUE,int=FALSE, main.txt=NULL,sub.txt=NULL,contour=FALSE,cuts=20,cex=1, cex.axes=1,xlab=NULL,ylab=NULL,zlab=NULL,xlim=NULL, ylim=NULL,zlim=NULL,margin.normal=FALSE,...) ```

## Arguments

 `x` object of class 'paircopula', result of function 'paircopula'. `val` Default val = NULL, one can calculate the estimated density/distribution for bivariate vector, e.g. val=c(0.5,1). `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 'K' and the value of lambda. `sub.txt` Default = NULL shows the log-likelihood, the penalized log-likelihood and the cAIC-value of the estimation. `contour` If TRUE, a contour plot is shown. Default = FALSE. `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. `xlim` Default = NULL, changes the range for the values of x in the case of a contour plot. `ylim` Default = NULL, changes the range for the values of y in the case of a contour plot. `zlim` Default = NULL and the range for the values of z are the range of calculated values. `margin.normal` Default = FALSE. If TRUE, the plot is presented with margins following standard normal distribution. `...` further arguments

## 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

Flexible Pair-Copula Estimation in D-vines using Bivariate Penalized Splines, Kauermann, G. and Schellhase, C. (2014), Statistics and Computing 24(6): 1081-1100).

Nonparametric estimation of simplified vines: comparison of methods, Nagler N., Schellhase, C. and Czado, C. (2017) Dependence Modeling.

penRvine documentation built on May 30, 2017, 2:20 a.m.