Nonparametric estimation with mixed data types in survey sampling

被引：4

作者：

Sanchez-Borrego, I. ^{[1
]}

Opsomer, J. D. ^{[2
]}

Rueda, M. ^{[1
]}

Arcos, A. ^{[1
]}

机构：

[1] Univ Granada, Dept Stat & Operat Res, Granada, Spain

[2] Colorado State Univ, Dept Stat, Ft Collins, CO 80523 USA

来源：

REVISTA MATEMATICA COMPLUTENSE | 2014年 / 27卷 / 02期

关键词：

Model-assisted estimation; Kernel regression; Survey sampling; Nonparametric regression; REGRESSION-FUNCTIONS; DISCRIMINATION; INFERENCE; MODEL;

D O I：

10.1007/s13163-013-0142-2

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

We consider the problem of finite population mean estimation with mixed data types. A model-assisted estimator based on nonparametric regression is proposed, which can handle discrete and continuous data and incorporates the sampling design in a natural manner. The proposed method shares the design-based properties of the kernel-based model-assisted estimator in the presence of continuous covariates and performs well under different scenarios in simulation experiments.

引用

页码：685 / 700

页数：16

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