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Activity Number: 83
Type: Contributed
Date/Time: Sunday, July 31, 2016 : 4:00 PM to 5:50 PM
Sponsor: International Chinese Statistical Association
Abstract #321470
Title: Simultaneous Confidence Band for Survey Data
Author(s): Jiangyan Wang* and Suojin Wang and Lijian Yang
Companies: Soochow University and Texas A&M University and Soochow University
Keywords: Bandwidth ; Brownian bridge ; Kernel ; Kolmogorov distribution ; Sample survey

Simultaneous confidence bands (SCBs) are proposed for the distribution functions of a finite population and the latent superpopulation via the empirical distribution function (nonsmooth) and kernel distribution estimator (KDE, smooth) based on a simple random sample (SRS), either with or without finite population correction. It is shown that both nonsmooth and smooth SCBs achieve asymptotically the nominal confidence level under standard assumptions. In particular, the uncorrected nonsmooth SCB for superpopulation is exactly the same as the Kolmogorov-Smirnov SCB based on an independent and identically distributed (iid) sample as long as the SRS size is infinitesimal relative to the finite population size. Extensive simulation studies confirm the asymptotic properties. As an illustration, the proposed SCBs are constructed for the population distribution of the well-known baseball data (Lohr 2009).

Authors who are presenting talks have a * after their name.

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