diagCOP | R Documentation |
Compute the primary diagonal or alternatively the secondary diagonal (Nelsen, 2006, pp. 12 and 16) of copula \mathbf{C}(u,v)
.
The primary diagonal is defined as
\mathbf{\delta}_\mathbf{C}(t) = \mathbf{C}(t,t)\mbox{,}
and the secondary diagonal is defined as
\mathbf{\delta}^{\star}_\mathbf{C}(t) = \mathbf{C}(t,1-t)\mbox{.}
Plotting is provided by this function because the diagonals are such important visual attributes of a copula. This function computes whole diagonals. If individual values are desired, then users are asked to use function calls along the diagonal such as COP(0.25,0.25, cop=P)
for the primary diagonal and COP(0.25,1-0.25, cop=P)
for the secondary diagonal, where for both examples the independence copula (uv = \mathbf{\Pi}
; P
) was chosen for purposes of clarification.
The \mathbf{\delta}_\mathbf{C}(t)
is related to order statistics of the multivariate sample (here bivariate) (Durante and Sempi, 2015, p. 68). The probability for the maxima is
\mathrm{Pr}[\mathrm{max}(u, v) \le t] = \mathbf{C}(t,t) = \mathbf{\delta}_\mathbf{C}(t) \mbox{\ and }
the probability for the minima is
\mathrm{Pr}[\mathrm{min}(u, v) \le t] = 2t - \mathbf{\delta}_\mathbf{C}(t)\mbox{.}
diagCOP(cop=NULL, para=NULL, secondary=FALSE,
ploton=TRUE, lines=TRUE, delt=0.005, ...)
cop |
A copula function; |
para |
Vector of parameters, if needed, to pass to the copula; |
secondary |
A logical to toggle the secondary diagonal; |
ploton |
A logical to toggle on the plot; |
lines |
Draw the lines of diagonal to the current device; |
delt |
The increment of the diagonal curve to plot, defaults to 0.5-percent intervals, which should be small enough to resolve fine curvature for many copulas in practice; and |
... |
Additional arguments to pass to the |
An R list
of the t
values, \mathbf{\delta}_\mathbf{C}(t,t)
(primary) or \mathbf{\delta}^{\star}_\mathbf{C}(t,1-t)
(secondary diagonal), along with a tag as to which diagonal is returned.
W.H. Asquith
Durante, F., and Sempi, C., 2015, Principles of copula theory: Boca Raton, CRC Press, 315 p.
Nelsen, R.B., 2006, An introduction to copulas: New York, Springer, 269 p.
diagCOPatf
, COP
, sectionCOP
## Not run:
# The primary diagonal of the W, P, M, and PSP copulas on the same plot
D <- diagCOP(cop=W, lwd=2)
D <- diagCOP(cop=P, lty=2, ploton=FALSE)
D <- diagCOP(cop=M, col=2, ploton=FALSE)
D <- diagCOP(cop=PSP, col=3, ploton=FALSE)
mtext("PRIMARY DIAGONAL OF SIMPLE COPULAS") # four primary diagonals
## End(Not run)
## Not run:
# The secondary diagonal of the W, P, M, and PSP copulas on the same plot
D <- diagCOP(cop=W, lwd=2, secondary=TRUE)
D <- diagCOP(cop=P, lty=2, secondary=TRUE, ploton=FALSE)
D <- diagCOP(cop=M, col=2, secondary=TRUE, ploton=FALSE)
D <- diagCOP(cop=PSP, col=3, secondary=TRUE, ploton=FALSE)
mtext("SECONDARY DIAGONAL OF SIMPLE COPULAS") # four secondary diagonals
## End(Not run)
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