Statistical summary of STRUCTURE output. STRUCTURE is a K-means clustering method for inferring population structure and assigning individuals to populations using genetic data. Pritchard JK, Stephens M, Donnelly PJ (2000) <DOI:10.1093/genetics/155.2.945>. <https://web.stanford.edu/group/pritchardlab/structure.html>.

After using this, a publication-ready correlation table with p-values
  indicated will be created.  The input can be a full data frame; any
  string and Boolean terms will be dropped as part of functionality.  Correlations and
  p-values are calculated using the 'Hmisc' framework.  Output of the 
  correlation_matrix() function is a table of strings; this gets saved out to a '.csv2'
  with the save_correlation_matrix() function for easy insertion into a paper.
  For more details about the process, consult
  <https://paulvanderlaken.com/2020/07/28/publication-ready-correlation-matrix-significance-r/>.

Modeling the correlation transitions under specified distributional assumptions within the realm of discretization in the context of the latency and threshold concepts. The details of the method are explained in Demirtas, H. and Vardar-Acar, C. (2017) <DOI:10.1007/978-981-10-3307-0_4>.

An investigative tool designed to help users visualize correlations between variables in their datasets. This package aims to provide an easy and effective way to explore and visualize these correlations, making it easier to interpret and communicate results.

Set of methods to constrain numerical series and time series within
             arbitrary boundaries.

There are 6 novel robust tests for equal correlation. They are all based on logistic regressions. The score statistic U is proportion to difference of two correlations based on different types of correlation in  6 methods. The ST1() is based on Pearson correlation. ST2() improved ST1() by using median absolute deviation. ST3() utilized type M correlation and ST4() used Spearman correlation.  ST5() and ST6() used two different ways to combine ST3() and ST4().  We highly recommend ST5() according to the article titled ''New Statistical Methods for Constructing Robust Differential Correlation Networks to characterize the interactions among microRNAs'' published in Scientific Reports.  Please see the reference: Yu et al. (2019) <doi:10.1038/s41598-019-40167-8>.