Anderson–Darling test¶
The null hypothesis of the Anderson–Darling test is that a dataset comes from a certain distribution; the reference distribution can be specified explicitely (onesample test). Ksample Anderson–Darling tests are available for testing whether several samples are coming from a single population drawn from the distribution function which does not have to be specified.

OneSampleADTest{T<:Real}(x::AbstractVector{T}, d::UnivariateDistribution)
Perform a one sample Anderson–Darling test of the null hypothesis that the data in vector
x
comes from the distributiond
against the alternative hypothesis that the sample is not drawn fromd
.Implements: pvalue

KSampleADTest{T<:Real}(xs::AbstractVector{T}...; modified=true)
Perform an ksample Anderson–Darling test of the null hypothesis that the data in vectors
xs
comes from the same distribution against the alternative hypothesis that the samples comes from different distributions.modified
paramater enables a modified test calculation for samples whose observations do not all coincide.Implements: pvalue
References:
 kSample AndersonDarling Tests, F. W. Scholz and M. A. Stephens, Journal of the American Statistical Association, Vol. 82, No. 399. (Sep., 1987), pp. 918924.