naginterfaces.library.nonpar.gofstat_​anddar_​unif

naginterfaces.library.nonpar.gofstat_anddar_unif(issort, y)

gofstat_anddar_unif calculates the Anderson–Darling goodness-of-fit test statistic and its probability for the case of standard uniformly distributed data.

For full information please refer to the NAG Library document for g08cj

https://www.nag.com/numeric/nl/nagdoc_29.3/flhtml/g08/g08cjf.html

Parameters

issortbool

Set $issort=True$ if the observations are sorted in ascending order; otherwise the function will sort the observations.

yfloat, array-like, shape $\left(n\right)$

$y_{\text{i}}$, for $\text{i}=1,2,\dots ,n$, the $n$ observations.

Returns

yfloat, ndarray, shape $\left(n\right)$

If $issort=False$, the data sorted in ascending order; otherwise the array is unchanged.

a2float

$A^2$, the Anderson–Darling test statistic.

pfloat

$p$, the upper tail probability for $A^2$.

Raises

NagValueError

(errno $1$)

On entry, $n=⟨value⟩$.

Constraint: $n>1$.

(errno $3$)

$issort=True$ and the data in $y$ is not sorted in ascending order.

(errno $9$)

The data in $y$ must lie in the interval $(0,1)$.

Notes

Calculates the Anderson–Darling test statistic $A^2$ (see gofstat_anddar()) and its upper tail probability by using the approximation method of Marsaglia and Marsaglia (2004) for the case of uniformly distributed data.

References

Anderson, T W and Darling, D A, 1952, Asymptotic theory of certain ‘goodness-of-fit’ criteria based on stochastic processes, Annals of Mathematical Statistics (23), 193–212

Marsaglia, G and Marsaglia, J, 2004, Evaluating the Anderson–Darling distribution, J. Statist. Software (9(2))