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.
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页码：685 / 700
页数：16
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