chi(data, nq = 100, qlim = NULL, alpha = 0.05, trunc = TRUE)## S3 method for class 'chi':
summary(object, digits=3, ...)
## S3 method for class 'chi':
plot(x, show=c("Chi"=TRUE,"ChiBar"=TRUE), lty=1, cilty=2, col=1, spcases=TRUE,
cicol=1, xlim=c(0, 1), ylimChi = c(-1, 1), ylimChiBar = c(-1, 1),
mainChi = "Chi", mainChiBar = "Chi Bar", xlab = "Quantile",
ylabChi = expression(chi(u)),#"Chi(u)"
ylabChiBar = expression(bar(chi)(u)), #"Chi Bar(u)"
ask, ...)
alpha = 0.05
.trunc = TRUE
.chi
.c("Chi" = TRUE, "ChiBar" = TRUE)
.FALSE
.chi
containing the following.Quantile
approaches 1 give an empirical measure of the type
and strength of tail dependendce exhibited by the data.
A limiting value of ChiBar equal to 1 indicates Asymptotic Dependence,
in which case the limiting value of Chi gives a measure of the strength
of dependence in this class. A limiting value of ChiBar of less than 1
indicates Asymptotic Independence in which case the limiting value of
ChiBar gives a measure of the strength of dependence.
The plot method shows the ChiBar and Chi functions. In the case of the
confidence interval for ChiBar excluding the value 1 for all of the largest
values of Quantile
, the plot of the Chi function is shown in grey.MCS
, rank
D <- liver[liver$dose == "D",]
chiD <- chi(D[, 5:6])
par(mfrow=c(1,2))
plot(chiD)
A <- liver[liver$dose == "A",]
chiA <- chi(A[, 5:6])
# here the limiting value of chi bar(u) lies away from one so the chi plot is not relevant and is plotted in grey
plot(chiA)
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