mexMonteCarlo {texmex} | R Documentation |
Simulation from dependence models
Description
Simulate Monte Carlo sample from a collection of fitted conditional dependence models.
Usage
mexMonteCarlo(nSample,mexList,mult=10)
Arguments
nSample |
Required sample size. |
mexList |
List of fitted dependence models (returned by
|
mult |
Integer specifying what multiple of the total number of points should be generated for rejection sample |
Details
Generates a Monte Carlo sample of the required size from a collection of conditional multivariate extreme values model of Heffernan and Tawn, 2004. For each marginal variable, the model that conditions on that margin is used to simulate values in the part of the sample space for which that margin is the largest of all marignal variables (measured on a quantile scale).
Value
A list with the following components:
nR |
For each margin, number of original Monte Carlo points replaced by points generated under the corresponding conditional model. |
MCsample |
Matrix contiaining the Monte Carlo sample, dimension
|
whichMax |
Vector of indices indicating which variable is largest (on the quantile scale) |
whichMaxAboveThresh |
Logical vector indicating which of the variables
identified by |
Author(s)
Harry Southworth, Janet E. Heffernan
References
J. E. Heffernan and J. A. Tawn, A conditional approach for multivariate extreme values, Journal of the Royal Statistical society B, 66, 497 – 546, 2004
Examples
mAll <- mexAll(winter,mqu=0.7,dqu=c(0.7,0.7,0.7,0.7,0.7))
mexMC <- mexMonteCarlo(5000,mAll)
pairs(mexMC$MCsample)