Adjusted Confidence Bands for Complex Survey Data

Confidence bands in nonparametric regression have been studied for a long time with data assumed to be generated from independent and identically distributed (iid) random variables. The methods and theoretical results for iid data, however, do not directly apply to data from stratified multistage sa...

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Bibliographic Details
Published inCommunications in statistics. Simulation and computation Vol. 45; no. 6; pp. 1896 - 1904
Main Authors Zhang, Guoyi, Gong, Maozhen, Cheng, Yang
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis 02.07.2016
Taylor & Francis Ltd
Subjects
Asymptotic methods
Complex surveys
Computer simulation
Confidence
Confidence bands
Confidence intervals
Kernels
Local linear estimator
Nonparametric regression
Primary 62
Random variables
Regression
Regression analysis
Samples
Sampling
Secondary 62D05
Simulations
Statistical analysis
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Summary:Confidence bands in nonparametric regression have been studied for a long time with data assumed to be generated from independent and identically distributed (iid) random variables. The methods and theoretical results for iid data, however, do not directly apply to data from stratified multistage samples. In this paper, we extend the confidence bands introduced by Zhang and Lu ( 2008 ) for iid case to complex surveys based on an entirely data-driven procedure; the proposed confidence bands incorporate both the sampling weights and the kernel weights. Simulation studies show that the proposed method works well.
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ISSN:0361-0918
1532-4141
DOI:10.1080/03610918.2014.882946