def ppcc_max(x, brack=(<NUM_LIT:0.0>,<NUM_LIT:1.0>), dist='<STR_LIT>'):
dist = _parse_dist_kw(dist)<EOL>osm_uniform = _calc_uniform_order_statistic_medians(x)<EOL>osr = sort(x)<EOL>def tempfunc(shape, mi, yvals, func):<EOL><INDENT>xvals = func(mi, shape)<EOL>r, prob = stats.pearsonr(xvals, yvals)<EOL>return <NUM_LIT:1>-r<EOL><DEDENT>return optimize.brent(tempfunc, brack=brack, args=(osm_uniform, osr, dist.ppf))<EOL>
Returns the shape parameter that maximizes the probability plot
    correlation coefficient for the given data to a one-parameter
    family of distributions.

    See also ppcc_plot