论文标题
放松“ bootcomb” r软件包中参数独立性假设
Relaxation of the parameter independence assumption in the `bootComb` R package
论文作者
论文摘要
背景。 BootComb R软件包允许研究人员在任意数量的独立估计参数的任意组合中得出正确的目标覆盖范围的置信区间。 BootComb的先前版本（<1.1.0）使用了独立的Bootstrap采样，并要求参数本身是独立的 - 在某些现实世界中的一个不切实际的假设。 发现。使用高斯copulas来定义参数之间的依赖性，已扩展了bootcomb软件包以允许依赖参数。 含义。现在，更新的bootcomb软件包可以处理因参数的案例，用户指定相关矩阵定义依赖性结构。虽然在实践中可能很难知道参数之间的确切依赖性结构，但``bootcomb''允许运行灵敏度分析以评估参数依赖对组合参数所得置信区间的影响。 可用性。 BootComb可从综合R档案网络（https://cran.r-project.org/package=bootcomb）获得。
Background. The bootComb R package allows researchers to derive confidence intervals with correct target coverage for arbitrary combinations of arbitrary numbers of independently estimated parameters. Previous versions (< 1.1.0) of bootComb used independent bootstrap sampling and required that the parameters themselves are independent - an unrealistic assumption in some real-world applications. Findings. Using Gaussian copulas to define the dependence between parameters, the bootComb package has been extended to allow for dependent parameters. Implications. The updated bootComb package can now handle cases of dependent parameters, with users specifying a correlation matrix defining the dependence structure. While in practice it may be difficult to know the exact dependence structure between parameters, `bootComb` allows running sensitivity analyses to assess the impact of parameter dependence on the resulting confidence interval for the combined parameter. Availability. bootComb is available from the Comprehensive R Archive Network (https://CRAN.R-project.org/package=bootComb).
