2026-06-01T17:48:46Zhttps://docta.ucm.es/rest/oai/request

oai:docta.ucm.es:20.500.14352/339992023-08-27T13:25:48Zcom_20.500.14352_14col_20.500.14352_15

Generalized Wald-type tests based on minimum density power divergence estimators Basu, A. Mandal, A. Martín, N. Pardo Llorente, Leandro 519.22 density power divergence robustness tests of hypotheses Estadística matemática (Matemáticas) 1209 Estadística 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 Depto. de Estadística e Investigación Operativa Fac. de Ciencias Matemáticas TRUE inpress 2023-06-19T13:33:10Z 2023-06-19T13:33:10Z 2015 journal article https://hdl.handle.net/20.500.14352/33999 0233-1888 eng MTM-2012-33740 ECO-2011- 25706 open access application/pdf Taylor & Francis Group Ltd