Vinecop.simulate¶
- Vinecop.simulate(self: pyvinecopulib.Vinecop, n: int, qrng: bool = False, num_threads: int = 1, seeds: List[int] = []) → numpy.ndarray[numpy.float64[m, n]]¶
Simulates from a vine copula model, see
inverse_rosenblatt()
.Simulated data is always a continous \(n \times d\) matrix.
- Parameter
n
: Number of observations.
- Parameter
qrng
: Set to true for quasi-random numbers.
- Parameter
num_threads
: The number of threads to use for computations; if greater than 1, the function will generate
n
samples concurrently innum_threads
batches.- Parameter
seeds
: Seeds of the random number generator; if empty (default), the random number generator is seeded randomly.
- Returns
An \(n \times d\) matrix of samples from the copula model.
- Parameter