data.frame
. This operation is very similiar to the plotting capabilities in level.curvesCOP
for level curves (Nelsen, 2006, pp. 12--13) but implemented in the function joint.curvesCOP
for alternative utility.For the case of a joint or probability, the dual of a copula (function) or $\tilde{\mathbf{C}}(u,v)$ from a copula (Nelsen, 2006, pp. 33--34) is used and symbolically the solution is:
$$\mathrm{Pr}[U \le v \mathrm{\ or\ } V \le v] = t = \tilde{\mathbf{C}}(u,v) = u + v - \mathbf{C}(u,v)\mbox{,}$$
where $U \mapsto [0, u_j, u_{j+1}, \cdots, t_i; \Delta t]$ (an irregular sequence of $u$ values from zero through to the $i$th value of $t$) and thus
$$t_i \mapsto \tilde{\mathbf{C}}(u=U, v)\mbox{,}$$
and solving for the sequence of $v$. The index $j$ is to indicate that a separate loop is involved and is distinct from $i$. The pairings ${u(t_i), v(t_i)}$ for each $t$ are packaged as an Rdata.frame
.
joint.curvesCOP(cop=NULL, para=NULL, type=c("and", "or"),
probs=c(0.5, 0.8, 0.90, 0.96, 0.98, 0.99, 0.995, 0.998),
zero2small=TRUE, small=1E-6, divisor=100, delu=0.001, ...)
small
value and exactly unity values for probability are converted to the value 1 - small
; this logical is useful if transformation from probabilzero2small
;duCOP
function of uniroot()
function in R.list
is returned with elements each of the given probs
.diagCOPatf
, duCOP
, jointCOP
, joint.curvesCOP2
, level.curvesCOP