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.

previous

scipy.stats.qmc.LatinHypercube.reset

next

scipy.stats.qmc.MultinomialQMC.fast_forward