Vinecop.cdf

Vinecop.cdf(self: pyvinecopulib.Vinecop, u: numpy.ndarray[numpy.float64[m, n]], N: int = 10000, num_threads: int = 1, seeds: List[int] = []) → numpy.ndarray[numpy.float64[m, 1]]

Evaluates the copula distribution.

Because no closed-form expression is available, the distribution is estimated numerically using Monte Carlo integration.

Parameter u:

An \(n \times (d + k)\) or \(n \times 2d\) matrix of evaluation points, where \(k\) is the number of discrete variables (see select()).

Parameter N:

Integer for the number of quasi-random numbers to draw to evaluate the distribution (default: 1e4).

Parameter num_threads:

The number of threads to use for computations; if greater than 1, the function will generate n samples concurrently in num_threads batches.

Parameter seeds:

Seeds to scramble the quasi-random numbers; if empty (default), the random number quasi-generator is seeded randomly.