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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/20673

    Title: The quasi-likelihood estimation in regression
    Authors: 吳忠武;Wu, Jong-wuu
    Contributors: 淡江大學統計學系
    Keywords: Regression parameter;quasi-likelihood model;link function;Monte Carlo simulation
    Date: 1996-06-01
    Issue Date: 2009-11-30 12:56:06 (UTC+8)
    Publisher: Springer
    Abstract: I propose a simply method to estimate the regression parameters in quasi-likelihood model My main approach utilizes the dimension reduction technique to first reduce the dimension of the regressor X to one dimension before solving the quasi-likelihood equations. In addition, the real advantage of using dimension reduction technique is that it provides a good initial estimate for one-step estimator of the regression parameters. Under certain design conditions, the estimators are asymptotically multivariate normal and consistent. Moreover, a Monte Carlo simulation is used to study the practical performance of the procedures, and I also assess the cost of CPU time for computing the estimates.
    Relation: Annals of the Institute of Statistical Mathematics 48(2), pp.283-294
    DOI: 10.1007/BF00054791
    Appears in Collections:[Graduate Institute & Department of Statistics] Journal Article

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