tailconCOP | R Documentation |
Compute the tail concentration function (q_\mathbf{C}
) of a copula \mathbf{C}(u,v)
(COP
) or diagnonal (diagCOP
) of a copula \delta_\mathbf{C}(t) = \mathbf{C}(t,t)
according to Durante and Semp (2015, p. 74):
q_\mathbf{C}(t) = \frac{\mathbf{C}(t,t)}{t} \cdot \mathbf{1}_{[0,0.5)} + \frac{1 - 2t + \mathbf{C}(t,t)}{1-t} \cdot \mathbf{1}_{[0.5, 1]}\mbox{\quad or}
q_\mathbf{C}(t) = \frac{\delta_\mathbf{C}(t)}{t} \cdot \mathbf{1}_{[0,0.5)} + \frac{1 - 2t + \delta_\mathbf{C}(t)}{1-t} \cdot \mathbf{1}_{[0.5, 1]}\mbox{,}
where t
is a nonexceedance probability on the margins and \mathbf{1}(.)
is an indicator function scoring 1 if condition is true otherwise zero on what interval t
resides: t \in [0,0.5)
or t \in [0.5,1]
. The q_\mathbf{C}(t; \mathbf{M}) = 1
for all t
for the M
copula and q_\mathbf{C}(t; \mathbf{W}) = 0
for all t
for the W
copula. Lastly, the function is related to the Blomqvist Beta (\beta_\mathbf{C}
; blomCOP
) by
q_\mathbf{C}(0.5) = (1 + \beta_\mathbf{C})/2\mbox{,}
where \beta_\mathbf{C} = 4\mathbf{C}(0.5, 0.5) - 1
. Lastly, the q_\mathbf{C}(t)
for 0,1 = t
is NaN
and no provision for alternative return is made. Readers are asked to note some of the mathematical similarity in this function to Blomqvist Betas in blomCOPss
in regards to tail dependency.
tailconCOP(t, cop=NULL, para=NULL, ...)
t |
Nonexceedance probabilities |
cop |
A copula function; |
para |
Vector of parameters or other data structure, if needed, to pass to the copula; and |
... |
Additional arguments to pass to the copula function. |
Value(s) for q_\mathbf{C}
are returned.
W.H. Asquith
Durante, F., and Sempi, C., 2015, Principles of copula theory: Boca Raton, CRC Press, 315 p.
taildepCOP
, tailordCOP
tailconCOP(0.5, cop=PSP) == (1 + blomCOP(cop=PSP)) / 2 # TRUE
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