Direction estimation in the single-index model with missing values

作者：Dong, Yuexiao^*; Zhu, Liping

来源：Statistics and Its Interface, 2013, 6(3): 379-385.

DOI：10.4310/sii.2013.v6.n3.a8

• Directional regression
• Missing at random
• Missing completely at random
• Sliced average variance estimation
• Sliced inverse regression

We cast direction estimation in the single-index model into the sufficient dimension reduction framework. Existing sufficient dimension reduction literature with missing values mainly focuses on sliced inverse regression and requires the missing at random (MAR) assumption. In this paper, we propose new methods to handle missing data based on sliced average variance estimation and directional regression. By examining different missingness schemes, we demonstrate that inverse probability weighted estimators for missing predictor are not sensitive to the MAR assumption. The fusion-refined procedures for missing response, on the other hand, may be outperformed by complete case analysis if the response is missing completely at random (MCAR).

• 出版日期2013
• 单位上海财经大学