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bundles / scipy latest / scipy / stats / _hypotests / _cdf_cvm

function

scipy.stats._hypotests:_cdf_cvm

source: /scipy/stats/_hypotests.py :494

Signature

def   _cdf_cvm ( x n = None * xp = None )

Summary

Calculate the cdf of the Cramér-von Mises statistic for a finite sample size n. If N is None, use the asymptotic cdf (n=inf).

Extended Summary

See equation 1.8 in Csörgő, S. and Faraway, J. (1996) for finite samples, 1.2 for the asymptotic cdf.

The function is not expected to be accurate for large values of x, say x > 2, when the cdf is very close to 1 and it might return values > 1 in that case, e.g. _cdf_cvm(2.0, 12) = 1.0000027556716846. Moreover, it is not accurate for small values of n, especially close to the bounds of the distribution's domain, [1/(12*n), n/3], where the value jumps to 0 and 1, respectively. These are limitations of the approximation by Csörgő and Faraway (1996) implemented in this function.

Aliases

  • scipy.stats._hypotests._cdf_cvm