The function may be called by the names: g01dac, nag_stat_normal_scores_exact or nag_normal_scores_exact.
If a sample of observations from any distribution (which may be denoted by ), is sorted into ascending order, the th smallest value in the sample is often referred to as the th ‘order statistic’, sometimes denoted by (see Kendall and Stuart (1969)).
The order statistics, therefore, have the property
(If , is the sample median.)
For samples originating from a known distribution, the distribution of each order statistic in a sample of given size may be determined. In particular, the expected values of the order statistics may be found by integration. If the sample arises from a Normal distribution, the expected values of the order statistics are referred to as the ‘Normal scores’. The Normal scores provide a set of reference values against which the order statistics of an actual data sample of the same size may be compared, to provide an indication of Normality for the sample.
A plot of the data against the scores gives a normal probability plot.
Normal scores have other applications; for instance, they are sometimes used as alternatives to ranks in nonparametric testing procedures.
g01dac computes the th Normal score for a given sample size as
and denotes the complete beta function.
The function attempts to evaluate the scores so that the estimated error in each score is less than the value etol specified by you. All integrations are performed in parallel and arranged so as to give good speed and reasonable accuracy.
Kendall M G and Stuart A (1969) The Advanced Theory of Statistics (Volume 1) (3rd Edition) Griffin
1: – IntegerInput
On entry: , the size of the set.
2: – doubleOutput
On exit: the Normal scores.
contains the value , for .
3: – doubleInput
On entry: the maximum value for the estimated absolute error in the computed scores.
4: – double *Output
On exit: a computed estimate of the maximum error in the computed scores (see Section 7).
5: – NagError *Input/Output
The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).
6Error Indicators and Warnings
Dynamic memory allocation failed.
See Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
On entry, argument had an illegal value.
The function was unable to estimate the scores with estimated
error less than etol. The best result obtained is returned together with the associated value of errest.
On entry, .
An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.
See Section 7.5 in the Introduction to the NAG Library CL Interface for further information.
Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library CL Interface for further information.
On entry, .
Errors are introduced by evaluation of the functions and errors in the numerical integration process. Errors are also introduced by the approximation of the true infinite range of integration by a finite range but and are chosen so that this effect is of lower order than that of the other two factors. In order to estimate the maximum error the functions are also integrated over the range . g01dac returns the estimated maximum error as
8Parallelism and Performance
g01dac is not threaded in any implementation.
The time taken by g01dac depends on etol and n. For a given value of etol the timing varies approximately linearly with n.
The program below generates the Normal scores for samples of size , , , and prints the scores and the computed error estimates.
This shows a Q-Q plot for a randomly generated set of data. The normal scores have been calculated using g01dac and the sample quantiles obtained by sorting the observed data using m01cac. A reference line at is also shown.