Description Usage Arguments Value References Examples
Bernstein copula simulation of a bivariate uniform distribution. The bivariate uniform distribution can be a transformed one from non-uniform data.
1 |
n |
An integer specifying the number of simulations required. |
diffEC |
Forward difference with respect of $x$ of the empirical copula matrix. Maybe computed with forwardDifference of empiricalCDF2Dcounts. empiricalCDF2Dcounts. |
u |
non-exceedance probabilities used for conditional simulation. Default to |
t |
Numeric value in |
delta |
numeric. Ideally must be zero, but it is used for numerical computation stability, say, |
... |
further arguments passed to uniroot |
a 2-columns matrix of simulated pseudo-observations u,v
.
Section 2.9 (Random Variate Generation) Nelsen, 2006
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | # Common to Examples 1, 2 and 3
en <- 100
library(copBasic)
set.seed(123); eu <- runif(en)
ev <- simCOPv(u = eu, cop=PLACKETTcop, para=20.1, snv=F) # simulate strong positive Plackett
plot.default(eu, ev, asp = 1, xlim = 0:1, ylim = 0:1, main = "data")
library(empiricalDistribution)
empCopulaCountsmatrix <- empiricalCDF2Dcounts(data.frame(U=eu, V=ev))
fDiffEmpCopMatrix <- forwardDifference(empCopulaCountsmatrix)
library(inverseFunction)
# Example 1 (n is given):
evMySim1 <- uvSim(n = en, diffEC = fDiffEmpCopMatrix)
plot.default(evMySim1, asp = 1, xlim = 0:1, ylim = 0:1, main = "Ex1")
# Example 2 (u is given):
evMySim2 <- uvSim(n = en, diffEC = fDiffEmpCopMatrix, u = eu)
plot.default(evMySim2, asp = 1, xlim = 0:1, ylim = 0:1, main = "Ex2")
# Example 3 (Reproducible Research, u and t are given):
et <- evMySim2[, 3]
evMySim3 <- uvSim(n = 100, diffEC = fDiffEmpCopMatrix, u = eu, t = et)
all.equal(evMySim2, evMySim3)
plot.default(evMySim3, asp = 1, xlim = 0:1, ylim = 0:1, main = "Ex3")
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