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首页> 外文期刊>Australian & New Zealand journal of statistics >A SEMIPARAMETRIC REGRESSION MODEL WITH MISSING COVARIATES IN CONTINUOUS-TIME CAPTURE-RECAPTURE STUDIES
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A SEMIPARAMETRIC REGRESSION MODEL WITH MISSING COVARIATES IN CONTINUOUS-TIME CAPTURE-RECAPTURE STUDIES

机译:连续捕获研究中具有变异协变量的半参数回归模型

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摘要

Covariate data were missing when a semiparametric regression model was used to study bird abundance in the Mai Po Sanctuary, Hong Kong. This paper proposes an EM-type algorithm to estimate the regression parameters for that study. Analytical calculation of the expectation in the EM method is difficult, or even impossible, especially when missing covariates are continuous. A Monte Carlo method is used in the EM algorithm to ease the calculation complexity. Asymptotic variances of the parameter estimates are also derived. Properties of the proposed estimators are assessed through numerical simulations and a real example.
机译:当使用半参数回归模型来研究香港米埔保护区的鸟类数量时,协变量数据缺失。本文提出了一种EM型算法来估计该研究的回归参数。 EM方法中期望值的分析计算非常困难,甚至是不可能的,尤其是在缺少协变量连续的情况下。 EM算法中使用了蒙特卡洛方法来减轻计算复杂度。还导出参数估计的渐近方差。拟议估计量的性质通过数值模拟和一个实际例子进行评估。

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