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合并响应数据的局部多项式回归

Local polynomial regression for pooled response data.

作者信息

Wang Dewei, Mou Xichen, Li Xiang, Huang Xianzheng

机构信息

Department of Statistics, University of South Carolina, Columbia, South Carolina, U.S.A.

Division of Epidemiology, Biostatistics, and Environmental Health, University of Memphis, Memphis, Tennessee, U.S.A.

出版信息

J Nonparametr Stat. 2020;32(4):814-837. doi: 10.1080/10485252.2020.1834104. Epub 2020 Nov 4.

DOI:10.1080/10485252.2020.1834104
PMID:33762800
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7986571/
Abstract

We propose local polynomial estimators for the conditional mean of a continuous response when only pooled response data are collected under different pooling designs. Asymptotic properties of these estimators are investigated and compared. Extensive simulation studies are carried out to compare finite sample performance of the proposed estimators under various model settings and pooling strategies. We apply the proposed local polynomial regression methods to two real-life applications to illustrate practical implementation and performance of the estimators for the mean function.

摘要

当仅在不同合并设计下收集合并响应数据时,我们提出了用于连续响应条件均值的局部多项式估计量。研究并比较了这些估计量的渐近性质。进行了广泛的模拟研究,以比较所提出的估计量在各种模型设置和合并策略下的有限样本性能。我们将所提出的局部多项式回归方法应用于两个实际应用中,以说明均值函数估计量的实际实现和性能。