Maximum approximate Bernstein likelihood estimates of the baseline density function and the regression coefficients in the proportional hazard regression models based on interval‐censored event time data result in smooth estimates of the survival functions which enjoys an almost n^1/2‐rate of convergence faster than the n^1/3‐rate for the existing estimates. The proposed method was shown by a simulation to have better finite sample performance than its main competitors. Some examples including real data are used to illustrate the usage of the proposed method.

中文翻译：

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区间删失数据的比例风险模型中的最大近似伯恩斯坦似然估计

基线密度函数的最大近似伯恩斯坦似然估计以及基于间隔删失事件时间数据的比例风险回归模型中的回归系数可对生存函数进行平滑估计，其收敛速度快于n ^1/2倍。现有估算值的n ^1/3比率。仿真结果表明，所提出的方法比其主要竞争对手具有更好的有限样本性能。一些包括实际数据的示例用于说明所提出方法的用法。