Variance Estimation for High-Dimensional Varying Index Coefficient Models

• 作者: Hao Lv Miao Wang Yicun Wang
• 来源期刊: 统计学期刊(英文)
• 学科: 数学
• 关键词: HIGH-DIMENSIONAL Data Refitted Cross-Validation VARYING INDEX COEFFICIENT MODELS Variance ESTIMATION
• 年，卷（期）: 2019,（5）
• 页码范围: 555-570
• 页数: 16页
• 分类号: O17

摘要

This paper studies the re-adjusted cross-validation method and a semiparametric regression model called the varying index coefficient model. We use the profile spline modal estimator method to estimate the coefficients of the parameter part of the Varying Index Coefficient Model (VICM), while the unknown function part uses the B-spline to expand. Moreover, we combine the above two estimation methods under the assumption of high-dimensional data. The results of data simulation and empirical analysis show that for the varying index coefficient model, the re-adjusted cross-validation method is better in terms of accuracy and stability than traditional methods based on ordinary least squares.