ON SOME CLASSES OF SELECTION PROCEDURES BASED ON RANKS.
PURDUE UNIV LAFAYETTE IND DEPT OF STATISTICS
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The paper deals with some nonrandomized ranking and selection procedures based on ranks using the subset selection approach. The main problem is to select a subset of k given populations, which contains the best population with probability at least P. The random variables associated with a fixed population are assumed to be independent identically distributed with a continuous distribution function depending on a single parameter. This parameter is assumed to stochastically order the k distribution functions, and the best population is the stochastically largest smallest population. The procedures presented depend on the individual observations of a given populations only through their ranks in the combined sample. In some preference-type tests or lost-data problems, these ranks may be the only information available to an experimenter. Author
- Statistics and Probability