English  |  正體中文  |  简体中文  |  Items with full text/Total items : 70585/70585 (100%)
Visitors : 23119176      Online Users : 633
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version

    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/27810

    Authors: CHU,CK;CHENG,KF
    Contributors: 統計研究所
    Date: 1995
    Issue Date: 2010-06-29 19:34:07 (UTC+8)
    Publisher: 中央大學
    Abstract: For random design nonparametric regression, in the case that the responses are binary and subject to misclassification, the performance of the kernel estimator is investigated. The kernel estimator is generally biased for the local proportion. To adjust for the bias, the double sampling scheme of Tenenbein (1970, 1971) is considered. A plugged-in kernel estimator and an imputed kernel estimator, which adjust for the effect of misclassification on the kernel estimator, are proposed, and their asymptotic mean squared errors are analysed. The plugged-in kernel estimator is better than the simple kernel estimator, which uses only the data without misclassification in the validation subsample, in the sense of having smaller asymptotic mean squared error. However, the imputed kernel estimator has smaller asymptotic variance. If the misclassification probabilities are constant, then the two proposed estimators have the same asymptotic bias. In this case, the imputed kernel estimator is always better than the plugged-in kernel estimator. For general misclassification probabilities, the asymptotic biases of the two proposed estimators are not comparable in magnitude. However, our simulation results demonstrate that, even when the misclassification probabilities are not constant, the imputed kernel estimator is still better for reasonable sample sizes.
    Relation: BIOMETRIKA
    Appears in Collections:[統計研究所] 期刊論文

    Files in This Item:

    File Description SizeFormat

    All items in NCUIR are protected by copyright, with all rights reserved.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback  - 隱私權政策聲明