Random partition indicator and spacing statistics
W. D. Kaigh · Communication in Statistics- Theory and Methods · 1996
Several conventional and new goodness-of-fit techniques are developed to assess random partitioning of a finite population into disjoint subsets. These nonparametric methods focus on indicator, spacing, and placement statistics. Mathematical development reminiscent of Fourier analysis yields distribution-free orthogonal indicator and spacing component goodness-of-fit procedures for simple random sampling assessment. Providing directional and omnibus criteria to detect between-subset differences, a main contribution of this survey is a unified treatment of the rank indicator procedures in Boos (1986) and the rank spacing methods in Kaigh (1994) with immediate applications to the nonparametric K-sample problem