NAG Library Routine Document

g08clf (gofstat_anddar_exp)


    1  Purpose
    7  Accuracy


g08clf calculates the Anderson–Darling goodness-of-fit test statistic and its probability for the case of an unspecified exponential distribution.


Fortran Interface
Subroutine g08clf ( n, issort, y, ybar, a2, aa2, p, ifail)
Integer, Intent (In):: n
Integer, Intent (Inout):: ifail
Real (Kind=nag_wp), Intent (In):: y(n)
Real (Kind=nag_wp), Intent (Out):: ybar, a2, aa2, p
Logical, Intent (In):: issort
C Header Interface
#include nagmk26.h
void  g08clf_ (const Integer *n, const logical *issort, const double y[], double *ybar, double *a2, double *aa2, double *p, Integer *ifail)


Calculates the Anderson–Darling test statistic A2 (see g08chf) and its upper tail probability for the small sample correction:
Adjusted ​ A2 = A2 1+0.6/n ,  
for n observations.


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
Stephens M A and D'Agostino R B (1986) Goodness-of-Fit Techniques Marcel Dekker, New York


1:     n – IntegerInput
On entry: n, the number of observations.
Constraint: n>1.
2:     issort – LogicalInput
On entry: set issort=.TRUE. if the observations are sorted in ascending order; otherwise the routine will sort the observations.
3:     yn – Real (Kind=nag_wp) arrayInput
On entry: yi, for i=1,2,,n, the n observations.
Constraint: if issort=.TRUE., values must be sorted in ascending order. Each yi must be greater than zero.
4:     ybar – Real (Kind=nag_wp)Output
On exit: the maximum likelihood estimate of mean.
5:     a2 – Real (Kind=nag_wp)Output
On exit: A2, the Anderson–Darling test statistic.
6:     aa2 – Real (Kind=nag_wp)Output
On exit: the adjusted A2.
7:     p – Real (Kind=nag_wp)Output
On exit: p, the upper tail probability for the adjusted A2.
8:     ifail – IntegerInput/Output
On entry: ifail must be set to 0, -1​ or ​1. If you are unfamiliar with this argument you should refer to Section 3.4 in How to Use the NAG Library and its Documentation for details.
For environments where it might be inappropriate to halt program execution when an error is detected, the value -1​ or ​1 is recommended. If the output of error messages is undesirable, then the value 1 is recommended. Otherwise, if you are not familiar with this argument, the recommended value is 0. 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).

Error Indicators and Warnings

If on entry ifail=0 or -1, explanatory error messages are output on the current error message unit (as defined by x04aaf).
Errors or warnings detected by the routine:
On entry, n=value.
Constraint: n>1.
issort=.TRUE. and the data in y is not sorted in ascending order.
The data in y must be greater than zero.
An unexpected error has been triggered by this routine. Please contact NAG.
See Section 3.9 in How to Use the NAG Library and its Documentation for further information.
Your licence key may have expired or may not have been installed correctly.
See Section 3.8 in How to Use the NAG Library and its Documentation for further information.
Dynamic memory allocation failed.
See Section 3.7 in How to Use the NAG Library and its Documentation for further information.


Probabilities are calculated using piecewise polynomial approximations to values estimated by simulation.

Parallelism and Performance

g08clf 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.

Further Comments



This example calculates the A2 statistics for data assumed to arise from an unspecified exponential distribution and calculates the p-value.

Program Text

Program Text (g08clfe.f90)

Program Data

Program Data (g08clfe.d)

Program Results

Program Results (g08clfe.r)

© The Numerical Algorithms Group Ltd, Oxford, UK. 2017