Conover W J (1980) Practical Nonparametric Statistics Wiley
Feller W (1948) On the Kolmogorov–Smirnov limit theorems for empirical distributions Ann. Math. Statist.19 179–181
Kendall M G and Stuart A (1973) The Advanced Theory of Statistics (Volume 2) (3rd Edition) Griffin
Siegel S (1956) Non-parametric Statistics for the Behavioral Sciences McGraw–Hill
Smirnov N (1948) Table for estimating the goodness of fit of empirical distributions Ann. Math. Statist.19 279–281
1: – IntegerInput
On entry: , the number of observations in the sample.
2: – Real (Kind=nag_wp)Input
On entry: contains the test statistic, or .
3: – IntegerInput/Output
On entry: ifail must be set to , or to set behaviour on detection of an error; these values have no effect when no error is detected.
A value of causes the printing of an error message and program execution will be halted; otherwise program execution continues. A value of means that an error message is printed while a value of means that it is not.
If halting is not appropriate, the value or is recommended. If message printing is undesirable, then the value is recommended. Otherwise, the value is recommended. When the value or is used it is essential to test the value of ifail on exit.
On exit: unless the routine detects an error or a warning has been flagged (see Section 6).
6Error Indicators and Warnings
If on entry or , explanatory error messages are output on the current error message unit (as defined by x04aaf).
Errors or warnings detected by the routine:
On entry, .
On entry, or : .
An unexpected error has been triggered by this routine. Please
See Section 7 in the Introduction to the NAG Library FL 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 FL Interface for further information.
Dynamic memory allocation failed.
See Section 9 in the Introduction to the NAG Library FL Interface for further information.
The large sample distribution used as an approximation to the exact distribution should have a relative error of less than % for most cases.
8Parallelism and Performance
g01eyf is not threaded in any implementation.
The upper tail probability for the two-sided statistic, , can be approximated by twice the probability returned via g01eyf, that is . (Note that if the probability from g01eyf is greater than then the two-sided probability should be truncated to ). This approximation to the tail probability for is good for small probabilities, (e.g., ) but becomes very poor for larger probabilities.
The time taken by the routine increases with , until . At this point the approximation is used and the time decreases significantly. The time then increases again modestly with .
The following example reads in different sample sizes and values for the test statistic . The upper tail probability is computed and printed for each case.