Generalized Wald-type tests based on minimum density power divergence estimators |
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Authors: | A Basu N Martin L Pardo |
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Institution: | 1. Indian Statistical Institute, Kolkata 700108, India;2. Department of Statistics, Carlos III University of Madrid, 28038 Getafe (Madrid), Spain;3. Department of Statistics and O.R. Complutense, University of Madrid, 28040 Madrid, Spain |
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Abstract: | 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 β. 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. |
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Keywords: | density power divergence robustness tests of hypotheses |
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