Overview
This chapter contains nonparametric statistics routines. Much about nonparametric statistics is also included in other chapters. Topics that can be found in other chapters are:
- Nonparametric measures of location and scale (Basic Statistics)
- Nonparametric measures in a contingency table (Categorical and Discrete Data Analysis)
- Measures of correlation in a contingency table (Correlation and Covariance)
- Tests of goodness of fit and randomness (Goodness of Fit)
Missing Values
Most routines in this chapter automatically handle missing values (NaN — not a number).
Tied Observations
Many of the routines described in this chapter contain a keyword FUZZ in the input. Observations that are within FUZZ of each other in absolute value are said to be tied. Moreover, in some routines, an observation within FUZZ of some value is said to be equal to that value. In the IMSL_WILCOXON, for example, such observations are eliminated from the analysis. If FUZZ = 0.0, observations must be identically equal before they are considered to be tied. Other positive values of FUZZ allow for numerical imprecision or roundoff error.
