Integer, Intent (In)	::	n
Integer, Intent (Inout)	::	ifail
Real (Kind=nag_wp), Intent (In)	::	x(n)
Real (Kind=nag_wp), Intent (Inout)	::	a(n)
Real (Kind=nag_wp), Intent (Out)	::	w, pw
Logical, Intent (In)	::	calwts

C Header Interface

#include <nag.h>

void	g01ddf_ (const double x[], const Integer n, const logical calwts, double a[], double w, double pw, Integer *ifail)

The routine may be called by the names g01ddf or nagf_stat_test_shapiro_wilk.

3 Description

g01ddf calculates Shapiro and Wilk's

W

statistic and its significance level for any sample size between

3

and

5000

. It is an adaptation of the Applied Statistics Algorithm AS R94, see Royston (1995). The full description of the theory behind this algorithm is given in Royston (1992).

Given a set of observations

x_{1}, x_{2}, \dots, x_{n}

sorted into either ascending or descending order (m01caf may be used to sort the data) this routine calculates the value of Shapiro and Wilk's

W

statistic defined as:

W = \frac{{(\sum_{i = 1}^{n} a_{i} x_{i})}^{2}}{\sum_{i = 1}^{n} {(x_{i} - \bar{x})}^{2}},

where

\bar{x} = \frac{1}{n} \sum_{1}^{n} x_{i}

is the sample mean and

a_{i}

, for

i = 1, 2, \dots, n

, are a set of ‘weights’ whose values depend only on the sample size

n

On exit, the values of

a_{i}

, for

i = 1, 2, \dots, n

, are only of interest should you wish to call the routine again to calculate

w

and its significance level for a different sample of the same size.

It is recommended that the routine is used in conjunction with a Normal

(Q - Q)

plot of the data. Routines g01daf and g01dbf can be used to obtain the required Normal scores.

4 References

Royston J P (1982) Algorithm AS 181: the

W

test for normality Appl. Statist. 31 176–180

Royston J P (1986) A remark on AS 181: the

W

test for normality Appl. Statist. 35 232–234

Royston J P (1992) Approximating the Shapiro–Wilk's

W

test for non-normality Statistics & Computing 2 117–119

Royston J P (1995) A remark on AS R94: A remark on Algorithm AS 181: the

W

test for normality Appl. Statist. 44(4) 547–551

5 Arguments

1: $x (n)$ – Real (Kind=nag_wp) array Input: On entry: the ordered sample values, $x_{i}$ , for $i = 1, 2, \dots, n$ .
2: $n$ – Integer Input: On entry: $n$ , the sample size.

Constraint: $3 \leq n \leq 5000$ .
3: $calwts$ – Logical Input: On entry: must be set to .TRUE. if you wish g01ddf to calculate the elements of a.
calwts should be set to .FALSE. if you have saved the values in a from a previous call to g01ddf.

If in doubt, set calwts equal to .TRUE..
4: $a (n)$ – Real (Kind=nag_wp) array Input/Output: On entry: if calwts has been set to .FALSE. then before entry a must contain the $n$ weights as calculated in a previous call to g01ddf, otherwise a need not be set.

On exit: the $n$ weights required to calculate $w$ .
5: $w$ – Real (Kind=nag_wp) Output: On exit: the value of the statistic, $w$ .
6: $pw$ – Real (Kind=nag_wp) Output: On exit: the significance level of $w$ .
7: $ifail$ – 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: $n \geq 3$ .

$ifail = 2$: On entry, $n = ⟨ value ⟩$ .
Constraint: $n \leq 5000$ .

$ifail = 3$: On entry, all elements of x are equal.

On entry, elements of x not in order. $x (⟨ value ⟩) = ⟨ value ⟩$ , $x (⟨ value ⟩) = ⟨ value ⟩$ , $x (⟨ value ⟩) = ⟨ value ⟩$ .

$ifail = - 99$: 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

There may be a loss of significant figures for large

n

8 Parallelism and Performance

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

g01ddf is not threaded in any implementation.

9 Further Comments

The time taken by g01ddf depends roughly linearly on the value of

n

For very small samples the power of the test may not be very high.

The contents of the array a should not be modified between calls to g01ddf for a given sample size, unless calwts is reset to .TRUE. before each call of g01ddf.

The Shapiro and Wilk's

W

test is very sensitive to ties. If the data has been rounded the test can be improved by using Sheppard's correction to adjust the sum of squares about the mean. This produces an adjusted value of

w

W A = W \frac{\sum {x_{(i)} - \bar{x}}^{2}}{{\sum_{i = 1}^{n} {x_{(i)} = \bar{x}}^{2} - \frac{n - 1}{12} ω^{2}}},

where

ω

is the rounding width.

W A

can be compared with a standard Normal distribution, but a further approximation is given by Royston (1986).

n > 5000

, a value for w and pw is returned, but its accuracy may not be acceptable. See Section 4 for more details.

10 Example

This example tests the following two samples (each of size

20

) for Normality.

Sample Number	Data
$1$	$0.11$ , $7.87$ , $4.61$ , $10.14$ , $7.95$ , $3.14$ , $0.46$ , $4.43$ , $0.21$ , $4.75$ , $0.71$ , $1.52$ , $3.24$ , $0.93$ , $0.42$ , $4.97$ , $9.53$ , $4.55$ , $0.47$ , $6.66$
$2$	$1.36$ , $1.14$ , $2.92$ , $2.55$ , $1.46$ , $1.06$ , $5.27$ , $- 1.11$ , $3.48$ , $1.10$ , $0.88$ , $- 0.51$ , $1.46$ , $0.52$ , $6.20$ , $1.69$ , $0.08$ , $3.67$ , $2.81$ , $3.49$

The elements of a are calculated only in the first call of g01ddf, and are re-used in the second call.

g01dd: FL CL CPP AD PY MB

NAG FL Interfaceg01ddf (test_​shapiro_​wilk)

▸▿ 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
g01ddf (test_shapiro_wilk)