Minimum Distance Estimation Based On The Kernels For U-Statistics

  • Park, Hyo-Il (Department of Applied Statistics, Chongju University, Chongju, Choongbook 360-764)
  • Published : 1998.03.01

Abstract

In this paper, we consider a minimum distance (M.D.) estimation based on kernels for U-statistics. We use Cramer-von Mises type distance function which measures the discrepancy between U-empirical distribution function(d.f.) and modeled d.f. of kernel. In the distance function, we allow various integrating measures, which can be finite, $\sigma$-finite or discrete. Then we derive the asymptotic normality and study the qualitative robustness of M. D. estimates.

Keywords

References

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