Description Usage Arguments Details Value See Also Examples
Calculate or plot the dependence function A for nine parametric bivariate extreme value models.
1 2 3 4 5 
x 
A vector of values at which the dependence function is
evaluated (ignored if plot or add is 
dep 
Dependence parameter for the logistic, asymmetric logistic, HuslerReiss, negative logistic and asymmetric negative logistic models. 
asy 
A vector of length two, containing the two asymmetry parameters for the asymmetric logistic and asymmetric negative logistic models. 
alpha, beta 
Alpha and beta parameters for the bilogistic, negative bilogistic, ColesTawn and asymmetric mixed models. 
model 
The specified model; a character string. Must be
either 
rev 
Logical; reverse the dependence function? This is
equivalent to evaluating the function at 
plot 
Logical; if 
add 
Logical; add to an existing plot? The existing plot
should have been created using either 
lty, blty 
Function and border line types. Set 
lwd, blwd 
Function an border line widths. 
col 
Line colour. 
xlim, ylim 
x and yaxis limits. 
xlab, ylab 
x and yaxis labels. 
... 
Other highlevel graphics parameters to be passed to

Any bivariate extreme value distribution can be written as
G(z1,z2) = exp{(y1+y2)A[y1/(y1+y2)]}
for some function A() defined on [0,1], where
yi = {1+si(ziai)/bi}^(1/si)
for 1+si(ziai)/bi > 0 and i = 1,2, with the (generalized extreme value) marginal parameters given by (ai,bi,si), bi > 0. If si = 0 then yi is defined by continuity.
A() is called (by some authors) the dependence function. It follows that A(0)=A(1)=1, and that A() is a convex function with max(x,1x) <= A(x) <= 1 for all 0 <= x <= 1. The lower and upper limits of A are obtained under complete dependence and independence respectively. A() does not depend on the marginal parameters.
Some authors take B(x) = A(1x) as the dependence function. If the
argument rev = TRUE
, then B(x) is plotted/evaluated.
abvevd
calculates or plots the dependence function
for one of nine parametric bivariate extreme value models,
at specified parameter values.
abvnonpar
, fbvevd
,
rbvevd
, amvevd
1 2 3 4 5 6 7 8  abvevd(dep = 2.7, model = "hr")
abvevd(seq(0,1,0.25), dep = 0.3, asy = c(.7,.9), model = "alog")
abvevd(alpha = 0.3, beta = 1.2, model = "negbi", plot = TRUE)
bvdata < rbvevd(100, dep = 0.7, model = "log")
M1 < fitted(fbvevd(bvdata, model = "log"))
abvevd(dep = M1["dep"], model = "log", plot = TRUE)
abvnonpar(data = bvdata, add = TRUE, lty = 2)

[1] 0.6444467
[1] 1.0000000 0.8272414 0.7012552 0.7841595 1.0000000
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