Castilla, E.; Martín, N.; Pardo, L.; Zografos, K. Composite Likelihood Methods Based on Minimum Density Power Divergence Estimator. Entropy2018, 20, 18.
Castilla, E.; Martín, N.; Pardo, L.; Zografos, K. Composite Likelihood Methods Based on Minimum Density Power Divergence Estimator. Entropy 2018, 20, 18.
Castilla, E.; Martín, N.; Pardo, L.; Zografos, K. Composite Likelihood Methods Based on Minimum Density Power Divergence Estimator. Entropy2018, 20, 18.
Castilla, E.; Martín, N.; Pardo, L.; Zografos, K. Composite Likelihood Methods Based on Minimum Density Power Divergence Estimator. Entropy 2018, 20, 18.
Abstract
In this paper a robust version of the Wald test statistic for composite likelihood is considered by using the composite minimum density power divergence estimator instead of the composite maximum likelihood estimator. This new family of test statistics will be called Wald-type test statistics. The problem of testing a simple and a composite null hypothesis is considered and the robustness is studied on the basis of a simulation study. Previously, the composite minimum density power divergence estimator is introduced and its asymptotic properties are studied.
Keywords
composite likelihood; maximum composite likelihood estimator; Wald test statistic; composite minimum density power divergence estimator;Wald-type test statistics.
Subject
Computer Science and Mathematics, Probability and Statistics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
