Robust Analysis of Variance Based Upon a Likelihood Ratio Criterion
针对线性模型中的一般线性假设，开发了似然比类型的稳健检验，并构造了类似经典平方和的数据分解，实现稳健方差分析。
Robust tests of general linear hypotheses in linear models are developed. These are likelihood ratio type tests in the same sense that M -estimates are maximum likelihood type estimates. Construction of the tests suggests a decomposition of the data into terms analogous to classical sums of squares, providing a robust analysis of variance. Asymptotic efficiency and robustness properties of the tests are the same as those of the M -estimates upon which they are based.