高维单分量偏最小二乘回归估计量的渐近分布

Pub Date : 2022-12-23 DOI:10.1002/cjs.11755

Jerónimo Basa, R. Dennis Cook, Liliana Forzani, Miguel Marcos

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引用次数: 0

摘要

：在线性回归模型的单分量偏最小二乘法中，随着样本量和预测因子数量的增加，我们确定了用户选择的系数估计器的单变量线性组合的渐近正态分布，并给出了相应的渐近置信度和预测区间。模拟研究和多巴胺数据集的分析用于支持我们的理论渐近结果及其实际应用。《加拿大统计杂志》xx:1-25；20？？©20？？加拿大统计学会

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Asymptotic distribution of one-component partial least squares regression estimators in high dimensions

In a one-component partial least squares fit of a linear regression model, we find the asymptotic normal distribution, as the sample size and number of predictors approach infinity, of a user-selected univariate linear combination of the coefficient estimator and give corresponding asymptotic confidence and prediction intervals. Simulation studies and an analysis of a dopamine dataset are used to support our theoretical asymptotic results and their practical application.

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