plot_ExtDep {ExtremalDep} | R Documentation |
Graphical summaries of parametric representations of extremal dependence.
Description
This function displays the angular density, Pickands dependence function and return levels for bivariate and trivariate extreme values models.
Usage
plot_ExtDep(object="angular", model, par, log=TRUE, data=NULL, contour=TRUE,
style, labels, cex.dat=1, cex.lab=1, cex.cont=1,
Q.fix, Q.range, Q.range0, cond=FALSE, ...)
Arguments
object |
A character string indicating which graphical summary to plot. Takes value |
model |
A string with the name of the model considered. Takes value |
par |
A vector representing the parameters of the model. |
log |
A logical value specifying if the log density is computed. Required when |
data |
A matrix representing angular data to be added to the density plot. Required when |
contour |
A logical value; if |
style |
A character string indicating the plotting style of the data. Takes value |
labels |
A vector of character strings indicating the labels. Must be of length |
cex.dat |
A positive real indicating the size of the data points. Required for the trivariate angular density. |
cex.lab |
A positive real indicating the size of the labels. |
cex.cont |
A positive real indicating the size of the contour labels. |
Q.fix |
A vector of length the dimension of the model, indicating some fixed quantiles to compute joint return levels. Must contain |
Q.range |
A vector or matrix indicating quantile values on the unit Frechet scale, for the components that are allowed to vary. Must be a vector or a one-column matrix if there is one |
Q.range0 |
A object of the same format as |
cond |
A logical value; if |
... |
Additional graphical arguments for the |
Details
The angular density is computed using the function dExtDep
with arguments method="Parametric"
and angular=TRUE
. The Pickands dependence function is computed using the function index.ExtDep
with argument object="pickands"
.
When displaying the bivariate angular density and some data are provided (a 2-column matrix is specified for data
), there is the choice to summarise the data using a histogram (style="hist"
) or to display the observations using tick marks (style="ticks"
).
When displaying return levels, there are two possibilities: univariate and bivariate return levels. Since the model dimensions are restricted to a maximum of three, in that case, aunivariate return level corresponds to fixing two components while a bivariate return level fixes only one component. The choice of the fixed component is decided by the position of the NA
value(s) in the Q.fix
argument. If par
is a vector then the corresponding return level(s) are printed. However if par
is a matrix then the return level(s) are evaluated for each value of the parameter vector and the mean, and empirical empirical interval are displayed. Typically this is used when posterior samples are available. When
par
is a matrix with only two rows, resulting plots may not provide much information.
When contours are displayed, levels are chosen to be the deciles.
Value
A graph depending on argument object
.
Author(s)
Simone Padoan, simone.padoan@unibocconi.it, https://faculty.unibocconi.it/simonepadoan/; Boris Beranger, borisberanger@gmail.com https://www.borisberanger.com;
See Also
Examples
data(pollution)
###############################
### Trivariate Husler-Reiss ###
###############################
f.hr <- fExtDep(method="PPP", data=PNS, model="HR", par.start=rep(1,3))
plot_ExtDep(object="angular", model="HR", par=f.hr$par, data=PNS,
labels=c(expression(PM[10]), expression(NO), expression(SO[2])),
cex.lab=2)
plot_ExtDep(object="pickands", model="HR", par=f.hr$par, data=PNS,
labels=c(expression(PM[10]), expression(NO), expression(SO[2])),
cex.lab=2) # Takes time!
###############################
### Bivariate Husler-Reiss ###
###############################
PN <- na.omit(Leeds.frechet[,1:2])
PN <- cbind(PN, rowSums(PN))
PN <- PN[order(PN[,3], decreasing = TRUE)[1:100],]
PN <- PN[,1:2]/PN[,3]
f.hr2 <- fExtDep(method="PPP", data=PN, model = "HR", par.start = 1)
plot_ExtDep(model="HR", par=f.hr2$par, log=FALSE, data=PN, style="hist")
plot_ExtDep(model="HR", par=f.hr2$par, log=FALSE, data=PN, style="ticks")
plot_ExtDep(object="pickands", model="HR", par=f.hr2$par)