Bicop.hfunc1_deriv

Bicop.hfunc1_deriv(self, u: numpy.ndarray, deriv: str, parameters: numpy.ndarray | None = None, num_threads: int = 1) → numpy.ndarray

Evaluates a first derivative of the first h-function \(h_1(u_1, u_2) = P(U_2 \le u_2 | U_1 = u_1)\).

deriv is one of "par1", "par2", … (short form "par"), "u1" (the conditioning argument), or "u2" (which equals the copula density).

Notes

If parameters is given, the copula is evaluated with a different parameter set per row of u instead of the stored parameters. parameters is then an (n, p) array with one row per row of u and p == len(self.parameters) columns, in the family’s natural (unrotated) parameterization, and the evaluation may be parallelized over num_threads. This is supported for parametric families only; a nonparametric family, a wrong shape, or non-finite or out-of-bounds values raise RuntimeError.