期刊
STATISTICS
卷 50, 期 1, 页码 1-26出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/02331888.2015.1016435
关键词
density power divergence; robustness; tests of hypotheses
资金
- [MTM-2012-33740]
- [ECO-2011-25706]
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.
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