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Module « scipy.stats »

Classe « MonteCarloMethod »

Informations générales

Héritage

builtins.object
    ResamplingMethod
        MonteCarloMethod

Définition

class MonteCarloMethod(ResamplingMethod):

help(MonteCarloMethod)

Configuration information for a Monte Carlo hypothesis test.

Instances of this class can be passed into the `method` parameter of some
hypothesis test functions to perform a Monte Carlo version of the
hypothesis tests.

Attributes
----------
n_resamples : int, optional
    The number of Monte Carlo samples to draw. Default is 9999.
batch : int, optional
    The number of Monte Carlo samples to process in each vectorized call to
    the statistic. Batch sizes >>1 tend to be faster when the statistic
    is vectorized, but memory usage scales linearly with the batch size.
    Default is ``None``, which processes all samples in a single batch.
rvs : callable or tuple of callables, optional
    A callable or sequence of callables that generates random variates
    under the null hypothesis. Each element of `rvs` must be a callable
    that accepts keyword argument ``size`` (e.g. ``rvs(size=(m, n))``) and
    returns an N-d array sample of that shape. If `rvs` is a sequence, the
    number of callables in `rvs` must match the number of samples passed
    to the hypothesis test in which the `MonteCarloMethod` is used. Default
    is ``None``, in which case the hypothesis test function chooses values
    to match the standard version of the hypothesis test. For example,
    the null hypothesis of `scipy.stats.pearsonr` is typically that the
    samples are drawn from the standard normal distribution, so
    ``rvs = (rng.normal, rng.normal)`` where
    ``rng = np.random.default_rng()``.
rng : `numpy.random.Generator`, optional
    Pseudorandom number generator state. When `rng` is None, a new
    `numpy.random.Generator` is created using entropy from the
    operating system. Types other than `numpy.random.Generator` are
    passed to `numpy.random.default_rng` to instantiate a ``Generator``.

Constructeur(s)

Signature du constructeur	Description
__init__(self, n_resamples=9999, batch=None, rvs=None, rng=None)

Opérateurs hérités de la classe object

__ge__, __gt__, __le__, __lt__, __ne__

Méthodes héritées de la classe ResamplingMethod

__init_subclass__, __subclasshook__

Méthodes héritées de la classe object

__delattr__, __dir__, __format__, __getattribute__, __getstate__, __hash__, __reduce__, __reduce_ex__, __setattr__, __sizeof__, __str__

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