kendallknight:肯德尔相关系数计算的高效实现

Mauricio Vargas Sepúlveda
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引用次数: 0

摘要

kendallknight 软件包引入了肯德尔相关系数计算的高效实现方法,在不牺牲准确性的前提下,显著改善了大型数据集的处理时间。kendallknight 软件包遵循 Knight (1966) 和后继文献,降低了计算复杂度,从而大幅减少了计算时间,将需要几分钟或几小时的操作转化为几毫秒或几分钟,同时保持了精度,并正确处理了边缘情况和错误。该软件包在计量经济学和统计领域尤其具有优势,因为这些领域需要快速、准确地计算肯德尔相关系数。基准测试表明,与基本 R 实现相比,该软件包的性能大幅提升,尤其是在大型数据集上。
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kendallknight: Efficient Implementation of Kendall's Correlation Coefficient Computation
The kendallknight package introduces an efficient implementation of Kendall's correlation coefficient computation, significantly improving the processing time for large datasets without sacrificing accuracy. The kendallknight package, following Knight (1966) and posterior literature, reduces the computational complexity resulting in drastic reductions in computation time, transforming operations that would take minutes or hours into milliseconds or minutes, while maintaining precision and correctly handling edge cases and errors. The package is particularly advantageous in econometric and statistical contexts where rapid and accurate calculation of Kendall's correlation coefficient is desirable. Benchmarks demonstrate substantial performance gains over the base R implementation, especially for large datasets.
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