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首页> 外文期刊>Communications in Statistics. B, Simulation and Computation >Bias Corrected Maximum Likelihood Estimatorunder The Generalized Linear Model for A Binary Variable
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Bias Corrected Maximum Likelihood Estimatorunder The Generalized Linear Model for A Binary Variable

机译:二元变量的广义线性模型下的偏差校正最大似然估计

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摘要

Under the generalized linear models for a binary variable, an approximate bias of the maximum likelihood estimator of the coefficient, that is a special case of linear parameter in Cordeiro and McCullagh (1991), is derived without a calculation of the third-order derivative of the log likelihood function. Using the obtained approximate bias of the maximum likelihood estimator, a bias-corrected maximum likelihood estimator is defined. Through a simulation study, we show that the bias-corrected maximum likelihood estimator and its variance estimator have a better performance than the maximum likelihood estimator and its variance estimator.
机译:在二元变量的广义线性模型下,无需计算的三阶导数,就可以得出系数的最大似然估计器的近似偏差,这是Cordeiro和McCullagh(1991)中线性参数的特例。对数似然函数。使用所获得的最大似然估计器的近似偏差,定义了经偏差校正的最大似然估计器。通过仿真研究,我们证明了经过偏差校正的最大似然估计器及其方差估计器比最大似然估计器及其方差估计器具有更好的性能。

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