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Asymptotics for statistical functionals of long-memory sequences
Authors:Eric Beutner  Wei Biao Wu  Henryk Zähle
Institution:
  • a Department of Quantitative Economics, Maastricht University, P.O. Box 616, NL-6200 MD Maastricht, The Netherlands
  • b Department of Statistics, The University of Chicago, 5734 S. University Avenue, Chicago, IL 60637, USA
  • c Department of Mathematics, Saarland University, Postfach 151150, D-66041 Saarbrücken, Germany
  • Abstract:We present two general results that can be used to obtain asymptotic properties for statistical functionals based on linear long-memory sequences. As examples for the first one we consider L- and V-statistics, in particular tail-dependent L-statistics as well as V-statistics with unbounded kernels. As an example for the second result we consider degenerate V-statistics. To prove these results we also establish a weak convergence result for empirical processes of linear long-memory sequences, which improves earlier ones.
    Keywords:Noncentral limit theorem  Linear long-memory sequence  Quasi-Hadamard differentiability  Modified Functional Delta Method  Weighted empirical process  L-statistic  U- and V-statistics  Degenerate V-statistic
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