Generalized Wald-type tests based on minimum density power divergence estimators Articles uri icon


  • Basu, A.
  • Mandal, A.
  • Pardo, L.

publication date

  • January 2016

start page

  • 1

end page

  • 26


  • 1


  • 50

International Standard Serial Number (ISSN)

  • 0233-1888

Electronic International Standard Serial Number (EISSN)

  • 1029-4910


  • In testing of hypothesis, the robustness of the tests is an important concern. Generally, the maximum likelihood-based tests are most efficient under standard regularity conditions, but they are highly non-robust even under small deviations from the assumed conditions. In this paper, we have proposed generalized Wald-type tests based on minimum density power divergence estimators for parametric hypotheses. This method avoids the use of nonparametric density estimation and the bandwidth selection. The trade-off between efficiency and robustness is controlled by a tuning parameter . The asymptotic distributions of the test statistics are chi-square with appropriate degrees of freedom. The performance of the proposed tests is explored through simulations and real data analysis.


  • density power divergence; robustness; tests of hypotheses; likelihood ratio tests; nonstandard conditions; hypotheses; robust