This paper estimates quantile differences for one sample with length-biased and right-censored (LBRC) data. To ensure the asymptotic unbiasedness of the estimator, the estimating equation method is adopted. To improve the efficiency of the estimator, in the sense of having a lower mean squared error, the kernel-smoothed approach is employed. To make full use of the features of LBRC data, the augmented inverse probability complete case weight is investigated in detail. Moreover, the consistency and asymptotic normality of the proposed estimators are established. The numerical simulations are conducted to examine the performance of the estimators.

中文翻译：

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用长度偏向和右删失的数据估计一个样本的分位数差异的方程估计

本文使用长度偏向和右删失（LBRC）数据估计一个样本的分位数差异。为了保证估计量的渐近无偏性，采用了估计方程法。为了提高估计器的效率，在均方误差较低的意义上，采用了核平滑方法。为了充分利用LBRC数据的特征，详细研究了增强的逆概率完整案例权重。此外，建立了所提出估计量的一致性和渐近正态性。进行数值模拟以检查估计器的性能。