get the p-value for the one-sided hypothesis ('less'
    or 'greater') or for the two-sided hypothesis ('two-sided').
    Defaults value is 'two-sided' .
distribution : 't' or 'normal', optional
    Whether to get the p-value by t-distribution or by standard normal
    distribution.
    Defaults value is 't' .

Returns
-------
statistic : float
    The Brunner-Munzer W statistic.
pvalue : float
    p-value assuming an t distribution. One-sided or
    two-sided, depending on the choice of `alternative` and `distribution`.

See Also
--------
mannwhitneyu : Mann-Whitney rank test on two samples.

Notes
-----
For more details on `brunnermunzel`, see `scipy.stats.brunnermunzel`.

Examples
--------
>>> from scipy.stats.mstats import brunnermunzel
>>> import numpy as np
>>> x1 = [1, 2, np.nan, np.nan, 1, 1, 1, 1, 1, 1, 2, 4, 1, 1]
>>> x2 = [3, 3, 4, 3, 1, 2, 3, 1, 1, 5, 4]
>>> brunnermunzel(x1, x2)
BrunnerMunzelResult(statistic=1.4723186918922935, pvalue=0.15479415300426624)  # may vary

r<