淡江大學機構典藏:Item 987654321/41306
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    題名: Rank estimating equations for partial spline models with monotonicity
    作者: 陳主智;Chen, Chu-chih;Hsieh, Fushing
    貢獻者: 淡江大學數學學系
    關鍵詞: Asymptotic relative efficiency;censored regression;rank analysis of covariance;rank transformation;semiparametric regression model
    日期: 1999
    上傳時間: 2010-01-28 07:15:14 (UTC+8)
    出版者: Taipei: Institute of Statistical Science, Academia Sinica
    摘要: For partial spline models with a monotone nonlinear component, a class of monotone estimating equations is proposed for estimating the slope parameters of the vector of covariables Z of the linear component, while adjusting for the corresponding ranks of the vector of covariables X of the nonlinear component. This approach avoids the technical complications due to the smoothing of estimators for the nonlinear component with monotonicity, as well as the curse of dimensionality. Also, computationally, our inferences do not involve the unknown error probability density function. As an R-estimator taking into account the rank correlation between Y and X, the asymptotic relative efficiency with respect to other estimators ignoring X is proportional to the Spearman correlation coefficient between them.
    關聯: Statistica Sinica 9(1), pp.199-210
    顯示於類別:[數學學系暨研究所] 期刊論文

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