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How Does the Dependence between Inspectors Impact Capture-Recapture Estimation? An Empirical Study

机译:检查员之间的依存关系如何影响捕获-重新捕获估计?实证研究

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Studies on Capture-recapture (CRC) method in software engineering suggested that the accuracy of the estimates were still far from satisfying. Although debates exist, researchers believe the dependence between different inspectors is one of the factors impacting the accuracy of CRC estimates. In this study, we apply linear correlation to measure the degree of dependence (measured by correlation coefficient, i.e., COV) between inspectors, based on which, we investigate the relation between COV and estimation accuracy (measure by Relative Error, i.e., RE) using the Unconditional Maximum Likelihood Estimator (Mt-UMLE) through nine sets of data from five papers. Besides, the confidence interval (CI)-(which is also an important indicator to reflect CRC estimating accuracy), may also be impacted by COV, to this end, we also investigated the relation between COV and CI. The major results show that: a) It is clear that there is an obviously inverse proportion on COV and CI, and when the COV=0, the radius of CI is almost in interval [1, 6] (exclude the outliers). b) There has also an inverse proportion with COV and RE, and the absolute value of RE increased with the absolute value of COV increased. So we can conclude that the accuracy of CRC estimates had been impacted by the dependence of inspectors. Our study suggested that the correlation cannot be ignored in the study of CRC.
机译:对软件工程中的捕获-捕获(CRC)方法的研究表明,估计的准确性仍远远不能令人满意。尽管存在争论,但研究人员认为,不同检查员之间的依赖性是影响CRC估算准确性的因素之一。在这项研究中,我们应用线性相关来衡量检查员之间的依赖程度(通过相关系数,即COV衡量),在此基础上,我们研究COV与估计准确性之间的关系(通过相对误差(即RE)衡量)通过五篇论文中的九组数据,使用无条件最大似然估计器(Mt-UMLE)。此外,置信区间(CI)-(也是反映CRC估计精度的重要指标)也可能受到COV的影响,为此,我们还研究了COV与CI之间的关系。主要结果表明:a)显然,COV和CI上存在明显的反比例,并且当COV = 0时,CI的半径几乎在区间[1,6]中(不包括异常值)。 b)与COV和RE也成反比,并且RE的绝对值随COV的绝对值增加而增加。因此,我们可以得出结论,CRC估计的准确性已受检查人员的依赖性影响。我们的研究表明,在CRC研究中,相关性不容忽视。

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