scipy.stats.qmc.MultinomialQMC¶

class scipy.stats.qmc.MultinomialQMC(pvals, *, engine=None, seed=None)[source]¶

QMC sampling from a multinomial distribution.

Parameters

pvalsarray_like (k,): Vector of probabilities of size k, where k is the number of categories. Elements must be non-negative and sum to 1.
engineQMCEngine, optional: Quasi-Monte Carlo engine sampler. If None, Sobol is used.
seed{None, int, numpy.random.Generator}, optional: If seed is None the numpy.random.Generator singleton is used. If seed is an int, a new Generator instance is used, seeded with seed. If seed is already a Generator instance then that instance is used.

Examples

>>> from scipy.stats import qmc
>>> engine = qmc.MultinomialQMC(pvals=[0.2, 0.4, 0.4])
>>> sample = engine.random(10)

Methods

`fast_forward`(n)	Fast-forward the sequence by n positions.
`random`([n])	Draw n QMC samples from the multinomial distribution.
`reset`()	Reset the engine to base state.