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.
nag_normal_scores_exact (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
On entry: , the size of the set.
On exit: the Normal scores.
contains the value , for .
On entry: the maximum value for the estimated absolute error in the computed scores.
– double *Output
On exit: a computed estimate of the maximum error in the computed scores (see Section 7).
– NagError *Input/Output
The NAG error argument (see Section 3.7 in How to Use the NAG Library and its Documentation).
Error Indicators and Warnings
Dynamic memory allocation failed.
See Section 184.108.40.206 in How to Use the NAG Library and its Documentation 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 2.7.6 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 2.7.5 in How to Use the NAG Library and its Documentation 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 . nag_normal_scores_exact (g01dac) returns the estimated maximum error as
Parallelism and Performance
nag_normal_scores_exact (g01dac) is not threaded in any implementation.
The time taken by nag_normal_scores_exact (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 nag_normal_scores_exact (g01dac) and the sample quantiles obtained by sorting the observed data using nag_double_sort (m01cac). A reference line at is also shown.