Testing semiparametric model-equivalence hypotheses based on the characteristic function

Feifei Chen, Simos G. Meintanis, Lixing Zhu*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review


We propose three test criteria each of which is appropriate for testing, respectively, the equivalence hypotheses of symmetry, homogeneity, and independence, with multivariate data. All quantities have the common feature of involving weighted-type distances between characteristic functions and are convenient from the computational point of view if the weight function is properly chosen. The asymptotic behaviour of the tests under the null and alternative hypotheses is investigated. Numerical studies and a real-data application are conducted in order to examine the performance of the criteria in finite samples.

Original languageEnglish
Pages (from-to)1158-1190
Number of pages33
JournalJournal of Statistical Computation and Simulation
Issue number6
Early online date15 Nov 2023
Publication statusPublished - 12 Apr 2024

Scopus Subject Areas

  • Statistics and Probability
  • Modelling and Simulation
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

User-Defined Keywords

  • characteristic function
  • equivalence test
  • independence testing
  • Neighborhood-of-model validation
  • symmetry testing
  • two-sample problem


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