abvalog(x = 0.5, dep, asy, plot = FALSE, border = TRUE, add = FALSE,
lty = 1, blty = 3, xlim = c(0, 1), ylim = c(0.5, 1), xlab = "",
ylab = "", ...)
abvaneglog(x = 0.5, dep, asy, plot = FALSE, border = TRUE, add = FALSE,
lty = 1, blty = 3, xlim = c(0, 1), ylim = c(0.5, 1), xlab = "",
ylab = "", ...)
abvhr(x = 0.5, dep, plot = FALSE, border = TRUE, add = FALSE,
lty = 1, blty = 3, xlim = c(0, 1), ylim = c(0.5, 1), xlab = "",
ylab = "", ...)
abvlog(x = 0.5, dep, plot = FALSE, border = TRUE, add = FALSE,
lty = 1, blty = 3, xlim = c(0, 1), ylim = c(0.5, 1), xlab = "",
ylab = "", ...)
abvneglog(x = 0.5, dep, plot = FALSE, border = TRUE, add = FALSE,
lty = 1, blty = 3, xlim = c(0, 1), ylim = c(0.5, 1), xlab = "",
ylab = "", ...)
TRUE
).TRUE
the function is plotted and
the values used to create the plot are returned invisibly.TRUE
a border representing the
maximal domain is added to the plot.plot
.abvlog
and abvalog
give the dependence function for the
logistic and asymmetric logistic models respectively.
abvneglog
and abvaneglog
give the dependence function
for the negative logistic and asymmetric negative logistic models
respectively.
abvhr
gives the dependence function for the Husler-Reiss
model.$A(\cdot)$ is called (by some authors) the dependence function. It follows that $A(0)=A(1)=1$, and that $A(\cdot)$ is a convex function with $\max(x,1-x) \leq A(x)\leq 1$ for all $0\leq x\leq1$. $A(\cdot)$ does not depend on the marginal parameters. $A(1/2)$ is returned by default since it is often a useful summary of dependence.
rbvalog
, rbvaneglog
,
rbvhr
, rbvlog
, rbvneglog
abvhr(dep = 2.7)
abvalog(dep = .3, asy = c(.7,.9))
abvalog(seq(0,1,0.25), dep = .3, asy = c(.7,.9))
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