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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/20727

    Title: Nonparametric smoothing in modeling logistic regression
    Authors: Lin, Kuo-chin;Chen, Yi-ju
    Contributors: 淡江大學統計學系
    Keywords: Cross-validation;cusum;local linear smoother;variable bandwidth
    Date: 2006-07-01
    Issue Date: 2009-11-30 12:57:54 (UTC+8)
    Publisher: New Delhi: TARU Publications
    Abstract: 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.
    Relation: Journal of Statistics & Management systems 9(2), pp.381-395
    DOI: 10.1080/09720510.2006.10701212
    Appears in Collections:[Graduate Institute & Department of Statistics] Journal Article

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