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# scipy.stats.anderson

`scipy.stats.``anderson`(x, dist='norm')

  Anderson-Darling test for data coming from a particular distribution

  The Anderson-Darling test is a modification of the Kolmogorov- Smirnov test kstest_ for the null hypothesis that a sample is drawn from a population that follows a particular distribution. For the Anderson-Darling test, the critical values depend on which distribution is being tested against. This function works for normal, exponential, logistic, or Gumbel (Extreme Value Type I) distributions.

  Parameters : | x : array_like array of sample data dist : {‘norm’,’expon’,’logistic’,’gumbel’,’extreme1’}, optional the type of distribution to test against. The default is ‘norm’ and ‘extreme1’ is a synonym for ‘gumbel’
  Returns : | A2 : float The Anderson-Darling test statistic critical : list The critical values for this distribution sig : list The significance levels for the corresponding critical values in percents. The function returns critical values for a differing set of significance levels depending on the distribution that is being tested against.

  Notes

  Critical values provided are for the following significance levels:

  normal/exponenential
    15%, 10%, 5%, 2.5%, 1%
  logistic
    25%, 10%, 5%, 2.5%, 1%, 0.5%
  Gumbel
    25%, 10%, 5%, 2.5%, 1%

  If A2 is larger than these critical values then for the corresponding significance level, the null hypothesis that the data come from the chosen distribution can be rejected.

  References

  [R160] | http://www.itl.nist.gov/div898/handbook/prc/section2/prc213.htm

  [R161] | Stephens, M. A. (1974). EDF Statistics for Goodness of Fit and Some Comparisons, Journal of the American Statistical Association, Vol. 69, pp. 730-737.

  [R162] | Stephens, M. A. (1976). Asymptotic Results for Goodness-of-Fit Statistics with Unknown Parameters, Annals of Statistics, Vol. 4, pp. 357-369.

  [R163] | Stephens, M. A. (1977). Goodness of Fit for the Extreme Value Distribution, Biometrika, Vol. 64, pp. 583-588.

  [R164] | Stephens, M. A. (1977). Goodness of Fit with Special Reference to Tests for Exponentiality , Technical Report No. 262, Department of Statistics, Stanford University, Stanford, CA.

  [R165] | Stephens, M. A. (1979). Tests of Fit for the Logistic Distribution Based on the Empirical Distribution Function, Biometrika, Vol. 66, pp. 591-595.

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