混合比例风险模型效率界的奇异性

G. Ridder, Tiemen Woutersen
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引用次数: 8

摘要

本文重新考虑了具有参数基线风险和回归函数的半参数混合比例风险模型的效率界。这个界限最早是由Hahn(1994)推导出来的。他的结果之一是,如果基线危害是威布尔,效率界是奇异的,即使模型是半参数识别的。这意味着威布尔参数和回归系数都不能在根N率下估计。我们证明Hahn的结果局限于一类在幂变换下封闭的模型。威布尔模型是这类模型中最突出的一个。给出了一个新的非参数辨识结果。该辨识结果允许混合分布的无穷平均值,并保证了效率界的非奇异性。这意味着根N估计是可能的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Singularity of the Efficiency Bound of the Mixed Proportional Hazard Model
We reconsider the efficiency bound for the semi-parametric Mixed Proportional Hazard (MPH) model with parametric baseline hazard and regression function. This bound was first derived by Hahn (1994). One of his results is that if the baseline hazard is Weibull, the efficiency bound is singular, even if the model is semi-parametrically identified. This implies that neither the Weibull parameter nor the regression coefficients can be estimated at the root N rate. We show that Hahn's results are confined to a class of models that is closed under the power transformation. The Weibull model is the most prominent model of this class. We also present a new nonparametric identification result. This identification results allows for infinite mean of the mixing distribution and ensures that the efficiency bound is nonsingular. This implies that root N estimation is possible.
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