Numerically determine the global property of the positively quadrant dependency (PQD) characteristic of a copula as described by Nelsen (2006, p. 188). The random variables \(X\) and \(Y\) are PQD if for all \((x,y)\) in \(\mathcal{R}^2\) when
\(H(x,y) \ge F(x)G(x)\) for all \((x,y)\) in \(\mathcal{R}^2\)
and thus by the copula \(\mathbf{C}(u,v) \ge uv\) for all \((u,v)\) in \(\mathcal{I}^2\). Alternatively, this means that \(\mathbf{C}(u,v) \ge \mathbf{\Pi}\), and thus it can be said that it is globally “greater” than independence (\(uv = \Pi\); P
).
Nelsen (2006) shows that a copula is PQD when
$$0 \le \beta_\mathbf{C} \mbox{,\ } 0 \le \gamma_\mathbf{C}\mbox{,\ and\ } 0 \le \rho_\mathbf{C} \le 3\tau_\mathbf{C}\mbox{,}$$
where \(\beta_\mathbf{C}\), \(\gamma_\mathbf{C}\), \(\rho_\mathbf{C}\), and \(\tau_\mathbf{C}\) are various copula measures of association or concordance that are respectively described in blomCOP
, giniCOP
, rhoCOP
, and tauCOP
.
The concept of negatively quadrant dependency (NQD) is the reverse: \(\mathbf{C}(u,v) \le \mathbf{\Pi}\) for all \((u,v)\) in \(\mathcal{I}^2\); so NQD is globally “smaller” than independence.
Conceptually, PQD is related to the probability that two random variables are simultaneously small (or simultaneously large) is at least as great as it would be if they were independent. The graph of a PQD copula lies on or above the copulatic surface of the independence copula \(\mathbf{\Pi}\), and conversely a NQD copula lies on or below \(\mathbf{\Pi}\).
Albeit a “global” property of a copula, there can be “local” variations in the PQD/NQD state. Points in \(\mathcal{I}^2\) where \(\mathbf{C}(u,v) - \mathbf{\Pi} \ge 0\) are locally PQD, whereas points in \(\mathcal{I}^2\) where \(\mathbf{C}(u,v) - \mathbf{\Pi} \le 0\) and locally NQD. Lastly, readers are directed to the last examples in wolfCOP
because as those examples involve the copulatic difference from independence \(\mathbf{C}(u,v) - \mathbf{\Pi} = \mathbf{C}(u,v) - \mathbf{\Pi}\) with 3-D renderings.
isCOP.PQD(cop=NULL, para=NULL, uv=NULL, empirical=FALSE, verbose=TRUE, ...)
If uv=NULL
then a logical for the global property of PQD is returned but if argument uv
is a data.frame
, then an R
list
is returned, and that list holds the global condition in global.PQD
and local condition assessments in local.PQD
and local.NQD
.
A copula function;
Vector of parameters or other data structure, if needed, to pass to the copula;
An optional R data.frame
of \(U\) and \(V\) nonexceedance probabilities \(u\) and \(v\) for the random variables \(X\) and \(Y\). This argument triggers different value return behavior (see Value);
A logical that will use sample versions for Gini Gamma, Spearman Rho, and Kendall Tau. This feature is only applicable if the copula is empirical and therefore the para
argument is the data.frame
of \(u\) and \(v\), which will be passed along to sample version functions instead of copula (see Note);
A logical that will report the four concordance measures; and
Additional arguments to pass, which are then passed to subordinate functions.
W.H. Asquith
Nelsen, R.B., 2006, An introduction to copulas: New York, Springer, 269 p.
blomCOP
, giniCOP
, rhoCOP
, tauCOP
, isCOP.LTD
, isCOP.RTI