Generating correlation matrices based on the boundaries of their coefficients

PLoS One. 2012;7(11):e48902. doi: 10.1371/journal.pone.0048902. Epub 2012 Nov 12.

Abstract

Correlation coefficients among multiple variables are commonly described in the form of matrices. Applications of such correlation matrices can be found in many fields, such as finance, engineering, statistics, and medicine. This article proposes an efficient way to sequentially obtain the theoretical bounds of correlation coefficients together with an algorithm to generate n × n correlation matrices using any bounded random variables. Interestingly, the correlation matrices generated by this method using uniform random variables as an example produce more extreme relationships among the variables than other methods, which might be useful for modeling complex biological systems where rare cases are very important.

MeSH terms

  • Algorithms
  • Biometry / methods*
  • Models, Statistical*
  • Probability
  • Reproducibility of Results
  • Statistical Distributions

Grants and funding

The authors have no support or funding to report.