Universidad Complutense de Madrid
E-Prints Complutense

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

Impacto

Downloads

Downloads per month over past year



Basu, A. and Mandal, A. and Martín, N. and Pardo Llorente, Leandro (2015) Generalized Wald-type tests based on minimum density power divergence estimators. Statistics: A Journal of Theoretical and Applied Statistics . ISSN 0233-1888 (In Press)

[img]
Preview
PDF
542kB

Official URL: http://www.tandfonline.com/loi/gsta20#.VS-ErvmsWCk




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


Item Type:Article
Uncontrolled Keywords:density power divergence; robustness; tests of hypotheses
Subjects:Sciences > Mathematics > Mathematical statistics
ID Code:29619
Deposited On:16 Apr 2015 09:46
Last Modified:16 Apr 2015 09:46

Origin of downloads

Repository Staff Only: item control page