A Robust Generalization of the Rao Test
基于最小密度功率散度估计，提出了新的Rao型检验统计量族，用于简单和复合零假设的稳健检验，理论推导了渐近分布和稳健性，数值验证表明其优于经典Rao检验。
This article presents new families of Rao-type test statistics based on the minimum density power divergence estimators which provide robust generalizations for testing simple and composite null hypotheses. The asymptotic null distributions of the proposed tests are obtained and their robustness properties are also theoretically studied. Numerical illustrations are provided to substantiate the theory developed. On the whole, the proposed tests are seen to be excellent alternatives to the classical Rao test as well as other well-known tests.