Chi-squared tests in kth-moment sufficient dimension reduction

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We present a novel approach to sufficient dimension reduction for the conditional kth moments in regression. The approach provides a computationally feasible test for the dimension of the central kth-moment subspace. In addition, we can test predictor effects without assuming any models. All test statistics proposed in the novel approach have asymptotic chi-squared distributions.

Original languageEnglish
Article numberA014
Pages (from-to)191-201
Number of pages11
JournalJournal of Statistical Computation and Simulation
Issue number1
StatePublished - 2013

Bibliographical note

Publisher Copyright:
© 2013 Taylor & Francis.


  • Chi-squared tests
  • Kth-moment dimension reduction
  • Predictor effect tests
  • Regression
  • Sufficient dimension reduction


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