well when the distribution of the predictors is heavy-tailed. In this paper, we propose two robust inverse regression … methods which are insensitive to data contamination: weighted inverse regression estimation and sliced inverse median … estimation. Both weighted inverse regression estimation and sliced inverse median estimation produce unbiased estimates of the …

considered. A new approach is proposed based on sliced inverse regression (SIR) for estimating the effective dimension reduction …

We apply the univariate sliced inverse regression to survival data. Our approach is different from the other papers on …

the sliced inverse regression (SIR) method. But in practice, some disadvantages appear such as the storage of the blocks …

structure of complex data. Sliced inverse regression is a well-known dimension reduction method for regression, which assumes an … eigenvalue problem. Sliced inverse regression is based on the strong assumptions on the data distribution and the form of … inverse regression method. However, each method is known to have its drawbacks either theoretically or empirically. To …

sample size. The new procedure is based on the optimal scoring interpretation of the sliced inverse regression method. As a …