ROBUST BOUNDED-INFLUENCE TESTS IN GENERAL PARAMETRIC MODELS
ROBUST BOUNDED-INFLUENCE TESTS IN GENERAL PARAMETRIC MODELS
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DOI：
10.1080/01621459.1994.10476822
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发表时间：
1994-09-01
影响因子：
3.7
通讯作者：
RONCHETTI, E
中科院分区：
文献类型：
--
作者：
HERITIER, S;RONCHETTI, E
我们引入稳健检验来检验一般参数模型中的假设。这些是Wald、Score和似然比检验的稳健版本，并且基于一般的M估计器。给出了它们的渐近性质和影响函数。证明了水平的稳定性是通过对相应的M估计的自标准化灵敏度的界来获得的。此外，还得到了Wald-型和Score-型检验的最优有界影响检验。给出了对真实和模拟数据集的应用，以说明测试的性能。
We introduce robust tests for testing hypotheses in a general parametric model. These are robust versions of the Wald, scores, and likelihood ratio tests and are based on general M estimators. Their asymptotic properties and influence functions are derived. It is shown that the stability of the level is obtained by bounding the self-standardized sensitivity of the corresponding M estimator. Furthermore, optimally bounded-influence tests are derived for the Wald- and scores-type tests. Applications to real and simulated data sets are given to illustrate the tests' performance.