py.random.Generator` are passed to
    `numpy.random.default_rng` to instantiate a ``Generator``  before use.
    If `rng` is already a ``Generator`` instance, then the provided instance is
    used. Specify `rng` for repeatable behavior.

    If this argument is passed by position, if `random_state` is passed by keyword
    into the initializer, or if the `random_state` attribute is used directly,
    legacy behavior for `random_state` applies:

    - If `random_state` is None (or `numpy.random`), the `numpy.random.RandomState`
      singleton is used.
    - If `random_state` is an int, a new ``RandomState`` instance is used,
      seeded with `random_state`.
    - If `random_state` is already a ``Generator`` or ``RandomState`` instance then
      that instance is used.

    .. versionchanged:: 1.15.0

        As part of the `SPEC-007 <https://scientific-python.org/specs/spec-0007/>`_
        transition from use of `numpy.random.RandomState` to
        `numpy.random.Generator`, this attribute name was changed from
        `random_state` to `rng`. For an interim period, both names will continue to
        work, although only one may be specified at a time. After the interim
        period, uses of `random_state` will emit warnings. The behavior of both
        `random_state` and `rng` are outlined above, but only `rng` should be used
        in new code.

method : {'BCa', 'percentile', 'basic'}
    Whether to use the 'percentile' bootstrap ('percentile'), the 'basic'
    (AKA 'reverse') bootstrap ('basic'), or the bias-corrected and
    accelerated bootstrap ('BCa', default).

rM