论文信息 - A moment estimate for rank statistics

A moment estimate for rank statistics

Abstract We show that higher moments for simple linear rank statistics behave very much in the same way as in the case of partial sums of independent, identically distributed random variables. This estimate is applied to compute the asymptotic efficacy of R-estimators when it is defined by risk functions.

Manfred Denker | M. Denker | U. Rösler | Uwe Rösler

[1] I. Ibragimov,et al. Independent and stationary sequences of random variables , 1971 .

[2] J. Doob. Stochastic processes , 1953 .

[3] J. Hájek,et al. Asymptotic Normality of Simple Linear Rank Statistics Under Alternatives II , 1968 .

[4] M. Denker,et al. SOME CONTRIBUTIONS TO CHERNOFF-SAVAGE THEOREMS , 1985 .

[5] R. Pyke,et al. Weak Convergence of a Two-sample Empirical Process and a New Approach to Chernoff-Savage Theorems , 1968 .

[6] B. Levit,et al. On the Efficiency of a Class of Non-Parametric Estimates , 1976 .

[7] P. Major. On the invariance principle for sums of independent identically distributed random variables , 1978 .

[8] J. L. Hodges,et al. Estimates of Location Based on Rank Tests , 1963 .

[9] G. Simons,et al. Inequalities for Ek(X, Y) when the marginals are fixed , 1976 .

[10] M. Denker,et al. A sharpening of the remainder term in the higher-dimensional central limit theorem for multilinear rank statistics , 1985 .