Integer, Intent (In)	::	n
Integer, Intent (Inout)	::	ifail
Real (Kind=nag_wp), Intent (Inout)	::	y(n)
Real (Kind=nag_wp), Intent (Out)	::	a2, p
Logical, Intent (In)	::	issort

C Header Interface

#include <nag.h>

void	g08cjf_ (const Integer n, const logical issort, double y[], double a2, double p, Integer *ifail)

The routine may be called by the names g08cjf or nagf_nonpar_gofstat_anddar_unif.

3 Description

Calculates the Anderson–Darling test statistic

A^{2}

(see g08chf) and its upper tail probability by using the approximation method of Marsaglia and Marsaglia (2004) for the case of uniformly distributed data.

4 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)

5 Arguments

1: $n$ – Integer Input: On entry: $n$ , the number of observations.

Constraint: $n > 1$ .
2: $issort$ – Logical Input: On entry: set $issort = .TRUE.$ if the observations are sorted in ascending order; otherwise the routine will sort the observations.
3: $y (n)$ – Real (Kind=nag_wp) array Input/Output: On entry: $y_{i}$ , for $i = 1, 2, \dots, n$ , the $n$ observations.

On exit: if $issort = .FALSE.$ , the data sorted in ascending order; otherwise the array is unchanged.

Constraint: if $issort = .TRUE.$ , the values must be sorted in ascending order. Each $y_{i}$ must lie in the interval $(0, 1)$ .
4: $a2$ – Real (Kind=nag_wp) Output: On exit: $A^{2}$ , the Anderson–Darling test statistic.
5: $p$ – Real (Kind=nag_wp) Output: On exit: $p$ , the upper tail probability for $A^{2}$ .
6: $ifail$ – Integer Input/Output: On entry: ifail must be set to $0$ , $−1$ or $1$ to set behaviour on detection of an error; these values have no effect when no error is detected.
A value of $0$ causes the printing of an error message and program execution will be halted; otherwise program execution continues. A value of $−1$ means that an error message is printed while a value of $1$ means that it is not.

If halting is not appropriate, the value $−1$ or $1$ is recommended. If message printing is undesirable, then the value $1$ is recommended. Otherwise, the value $0$ is recommended. When the value $- 1$ or $1$ is used it is essential to test the value of ifail on exit.

On exit: $ifail = 0$ unless the routine detects an error or a warning has been flagged (see Section 6).

6 Error Indicators and Warnings

If on entry

ifail = 0

−1

, explanatory error messages are output on the current error message unit (as defined by x04aaf).

Errors or warnings detected by the routine:

$ifail = 1$: On entry, $n = ⟨ value ⟩$ .
Constraint: $n > 1$ .

$ifail = 3$: $issort = .TRUE.$ and the data in y is not sorted in ascending order.

$ifail = 9$: The data in y must lie in the interval $(0, 1)$ .

$ifail = - 99$: An unexpected error has been triggered by this routine. Please contact NAG.
See Section 7 in the Introduction to the NAG Library FL Interface for further information.

$ifail = - 399$: Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library FL Interface for further information.

$ifail = - 999$: Dynamic memory allocation failed.
See Section 9 in the Introduction to the NAG Library FL Interface for further information.

7 Accuracy

Probabilities greater than approximately

0.09

are accurate to five decimal places; lower value probabilities are accurate to six decimal places.

8 Parallelism and Performance

Background information to multithreading can be found in the Multithreading documentation.

g08cjf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.

Please consult the X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this routine. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

9 Further Comments

None.

10 Example

This example calculates the

A^{2}

statistic and its

p

-value for uniform data obtained by transforming exponential variates.

g08cj: FL CL CPP AD PY MB

NAG FL Interfaceg08cjf (gofstat_​anddar_​unif)

▸▿ Contents

1 Purpose

2 Specification

3 Description

4 References

5 Arguments

6 Error Indicators and Warnings

7 Accuracy

8 Parallelism and Performance

9 Further Comments

10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results

NAG FL Interface
g08cjf (gofstat_anddar_unif)