论文标题
Kendall的tau估计器用于双变量零充气计数数据
Kendall's tau estimator for bivariate zero-inflated count data
论文作者
论文摘要
在本文中，我们扩展了Pimentel等人的工作。 （2015年），并提出了针对双变量零充气计数数据的Kendall $τ$的调整后的估计器。我们提供了提议的估计器的可实现的下限和上限，并显示了它与当前文献的关系。此外，我们还建议对可实现的界限进行估计，从而帮助从业者在使用真实数据时解释结果。与Pimentel等人的未经调整的估计器相比，肯德尔$τ$的拟议估计器的性能没有偏见。 （2015）。我们的结果还表明，当缺乏边际分布的知识时，可以使用界限估计器。
In this paper, we extend the work of Pimentel et al. (2015) and propose an adjusted estimator of Kendall's $τ$ for bivariate zero-inflated count data. We provide achievable lower and upper bounds of our proposed estimator and show its relationship with current literature. In addition, we also suggest an estimator of the achievable bounds, thereby helping practitioners interpret the results while working with real data. The performance of the proposed estimator for Kendall's $τ$ is unbiased with smaller mean squared errors compared to the unadjusted estimator of Pimentel et al. (2015). Our results also show that the bound estimator can be used when knowledge of the marginal distributions is lacking.
