Calculates the co-ranking matrix to assess the
    quality of a dimensionality reduction.

Allows the user to apply nice color gradients to 'shiny' elements.
    The gradients are extracted from the 'colorffy' website. See <https://www.colorffy.com/gradients/catalog>.

We design algorithms with linear time complexity with respect to the dimension for three commonly studied correlation structures, including exchangeable, decaying-product and K-dependent correlation structures, and extend the algorithms to generate binary data of general non-negative correlation matrices with quadratic time complexity. Jiang, W., Song, S.,  Hou, L. and Zhao, H. "A set of efficient methods to generate high-dimensional binary data with specified correlation structures." The American Statistician. See <doi:10.1080/00031305.2020.1816213> for a detailed presentation of the method.

Corbae-Ouliaris frequency domain filtering. According to 
             Corbae and Ouliaris (2006) <doi:10.1017/CBO9781139164863.008>,
             this is a solution for extracting cycles from time series, like
             business cycles etc. when filtering. This method is valid for both
             stationary and non-stationary time series.

Perform a correlational class analysis of the data, resulting in a partition of the data into separate modules.

Partitions data points (variables) into communities/clusters, 
    similar to clustering algorithms such as k-means and hierarchical 
    clustering. This package implements a clustering algorithm based on a new 
    metric CORD, defined for high-dimensional parametric or semiparametric 
    distributions. For more details see Bunea et al. (2020), Annals of Statistics 
    <doi:10.1214/18-AOS1794>.

Functions for calculating the OPTICS Cordillera. The OPTICS Cordillera measures the amount of 'clusteredness' in a numeric data matrix within a distance-density based framework for a given minimum number of points comprising a cluster, as described in Rusch, Hornik, Mair (2018) <doi:10.1080/10618600.2017.1349664>. We provide an R native version with methods for printing, summarizing, and plotting the result.