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    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/20727

    题名: Nonparametric smoothing in modeling logistic regression
    作者: Lin, Kuo-chin;Chen, Yi-ju
    贡献者: 淡江大學統計學系
    关键词: Cross-validation;cusum;local linear smoother;variable bandwidth
    日期: 2006-07-01
    上传时间: 2009-11-30 12:57:54 (UTC+8)
    出版者: New Delhi: TARU Publications
    摘要: This paper is emphasized on the logistic regression model fit with continuous and categorical covariates. A test statistic based on non-parametric local linear regression technique with optimal bandwidth which is chosen by cross validation method is proposed. This proposed test does not require a space partition of covariates or groups of the fitted values to compensate a small expected cell size. The expectation and variance of the proposed test statistic are computed and the sampling distributions of test statistic for various of logistic regression models are evaluated. We use simulations to compare the power of the new test with that of the current assessing methods for different logistic models. The proposed method is illustrated by using data from Caplehorn (1991) for the heroin addicts.
    關聯: Journal of Statistics & Management systems 9(2), pp.381-395
    DOI: 10.1080/09720510.2006.10701212
    显示于类别:[統計學系暨研究所] 期刊論文


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