Abstract

We propose an estimation method, named functional average variance estimation (FAVE), for estimating the EDR space in functional semiparametric regression model, based on kernel estimates of density and regression. Consistency results are then established for the estimator of the interest operator, and for the directions of EDR space. A simulation study that shows that the proposed approach performs better than traditional ones is presented.

中文翻译：

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使用函数数据进行降维的平滑平均方差估计

摘要

我们提出了一种名为函数平均方差估计 (FAVE) 的估计方法，用于基于密度和回归的核估计来估计函数半参数回归模型中的 EDR 空间。然后为兴趣算子的估计器和 EDR 空间的方向建立一致性结果。仿真研究表明所提出的方法比传统方法性能更好。