Nothing
testStat_T2c <- function(env)
{
# Computation of the pseudos-observations
ecdf1 = stats::ecdf(env$X1)
ecdf2 = stats::ecdf(env$X2)
ecdf3 = stats::ecdf(env$X3)
env$U1 = ecdf1(env$X1)
env$U2 = ecdf2(env$X2)
env$U3 = ecdf3(env$X3)
# Computation of Z
env$resultZ = estimationOfZ_I_J(U1 = env$U1, U2 = env$U2, U3 = env$U3,
kernel = env$kernel.name, h = env$h)
env$Z1 = env$resultZ$Z1
env$Z2 = env$resultZ$Z2
env$matrixK3 = env$resultZ$matrixK3
# Estimation by conditional CMLE
if (env$family == 2) {
env$theta_0 = VineCopula::BiCopEst(u1 = env$Z1, u2 = env$Z2,
family = 1 , method = "itau")$par
env$theta_xJ = estimateParCondCopula_ZIJ(
Z1_J = env$Z1, Z2_J = env$Z2,
observedX3 = env$U3, newX3 = env$grid$nodes,
family = 1 , method = "itau",
h = env$h)
} else {
env$theta_0 = VineCopula::BiCopEst(u1 = env$Z1, u2 = env$Z2,
family = env$family , method = "mle")$par
env$theta_xJ = estimateParCondCopula_ZIJ(
Z1_J = env$Z1, Z2_J = env$Z2,
observedX3 = env$U3, newX3 = env$grid$nodes,
family = env$family , method = "mle",
h = env$h)
}
env$true_stat = sum( env$grid$weights * (env$theta_0 - env$theta_xJ)^2)
}
testStat_T2c_boot1st <- function(env)
{
if (is.null(env$existZU_st)) {
# Computation of the pseudos-observations
ecdf1_st = stats::ecdf(env$X1_st)
ecdf2_st = stats::ecdf(env$X2_st)
ecdf3_st = stats::ecdf(env$X3_st)
env$U1_st = ecdf1_st(env$X1_st)
env$U2_st = ecdf2_st(env$X2_st)
env$U3_st = ecdf3_st(env$X3_st)
# Computation of Z
env$resultZ_st = estimationOfZ_I_J(U1 = env$U1_st, U2 = env$U2_st, U3 = env$U3_st,
kernel = env$kernel.name, h = env$h)
env$Z1_st = env$resultZ_st$Z1
env$Z2_st = env$resultZ_st$Z2
}
# Estimation by conditional CMLE
if (env$family == 2) {
env$theta_0_st = VineCopula::BiCopEst(u1 = env$Z1_st, u2 = env$Z2_st,
family = 1 , method = "itau")$par
env$theta_xJ_st = estimateParCondCopula_ZIJ(
Z1_J = env$Z1_st, Z2_J = env$Z2_st,
observedX3 = env$U3_st, newX3 = env$grid$nodes,
family = 1 , method = "itau",
h = env$h)
} else {
env$theta_0_st = VineCopula::BiCopEst(u1 = env$Z1_st, u2 = env$Z2_st,
family = env$family , method = "mle")$par
env$theta_xJ_st = estimateParCondCopula_ZIJ(
Z1_J = env$Z1_st, Z2_J = env$Z2_st,
observedX3 = env$U3_st, newX3 = env$grid$nodes,
family = env$family , method = "mle",
h = env$h)
}
env$stat_st = sum(env$grid$weights *
(env$theta_xJ_st - env$theta_xJ - env$theta_0_st + env$theta_0)^2)
}
testStat_T2c_boot2st <- function(env)
{
if (is.null(env$existZU_st)) {
# Computation of the pseudos-observations
ecdf1_st = stats::ecdf(env$X1_st)
ecdf2_st = stats::ecdf(env$X2_st)
ecdf3_st = stats::ecdf(env$X3_st)
env$U1_st = ecdf1_st(env$X1_st)
env$U2_st = ecdf2_st(env$X2_st)
env$U3_st = ecdf3_st(env$X3_st)
# Computation of Z
env$resultZ_st = estimationOfZ_I_J(U1 = env$U1_st, U2 = env$U2_st, U3 = env$U3_st,
kernel = env$kernel.name, h = env$h)
env$Z1_st = env$resultZ_st$Z1
env$Z2_st = env$resultZ_st$Z2
}
# Estimation by conditional CMLE
if (env$family == 2) {
env$theta_0_st = VineCopula::BiCopEst(u1 = env$Z1_st, u2 = env$Z2_st,
family = 1 , method = "itau")$par
env$theta_xJ_st = estimateParCondCopula_ZIJ(
Z1_J = env$Z1_st, Z2_J = env$Z2_st,
observedX3 = env$U3_st, newX3 = env$grid$nodes,
family = 1 , method = "itau",
h = env$h)
} else {
env$theta_0_st = VineCopula::BiCopEst(u1 = env$Z1_st, u2 = env$Z2_st,
family = env$family , method = "mle")$par
env$theta_xJ_st = estimateParCondCopula_ZIJ(
Z1_J = env$Z1_st, Z2_J = env$Z2_st,
observedX3 = env$U3_st, newX3 = env$grid$nodes,
family = env$family , method = "mle",
h = env$h)
}
env$stat_st = sum(env$grid$weights *
(env$theta_xJ_st - env$theta_0_st)^2)
}
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