kendallknight: An R Package for Efficient Implementation of Kendall's Correlation Coefficient Computation

TL;DR

The kendallknight R package provides a highly efficient and accurate implementation of Kendall's correlation coefficient, drastically reducing computation time for large datasets in econometric and statistical analyses.

Contribution

It introduces an optimized algorithm for Kendall's correlation, significantly improving speed over existing R implementations while maintaining accuracy.

Findings

Substantial performance improvements over base R implementation.

Effective handling of large datasets with reduced computation time.

Maintains accuracy and handles edge cases correctly.

Abstract

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.