Representations, conversions and display of orientation SO(3) data.
 See the orientlib help topic for details.

A general framework for the application of cross-validation schemes
    to particular functions. By allowing arbitrary lists of results, origami
    accommodates a range of cross-validation applications. This implementation
    was first described by Coyle and Hejazi (2018) <doi:10.21105/joss.00512>.

A visualization tool for multivariate data. This package maintains the original functionality of a radar chart and avoids potential misuse of its connected regions, with newly added features to better assist multi-criteria decision-making.

Automatically adding 'pkg::' to a function, i.e. mutate()
    becomes dplyr::mutate(). It is up to the user to determine which
    packages should be used explicitly, whether to include base R packages
    or use the functionality on selected text, a file, or a complete
    directory. User friendly logging is provided in the 'RStudio' Markers
    pane. Lives in the spirit of 'lintr' and 'styler'. Can also be used
    for checking which packages are actually used in a project.

Functions to handle ordinal relations reflected within the feature space. Those function allow to search for ordinal relations in multi-class datasets. One can check whether proposed relations are reflected in a specific feature representation. Furthermore, it provides functions to filter, organize and further analyze those ordinal relations.

Obtaining Bayes Expected A Posteriori (EAP) individual score 
    estimates based on linear and non-linear extended Exploratoy Factor Analysis
    solutions that include a correlated-residual structure.

Algorithm of online regularized k-means to deal with online multi(single) view data.
 The philosophy of the package is described in Guo G. (2024) 
 <doi:10.1016/j.ins.2024.121133>.

Objects and methods to handle and solve the min-sum location problem, also known as Fermat-Weber problem. The min-sum location problem search for a point such that the weighted sum of the distances to the demand points are minimized. See "The Fermat-Weber location problem revisited" by Brimberg, Mathematical Programming, 1, pg. 71-76, 1995. <DOI:10.1007/BF01592245>.
	     General global optimization algorithms are used to solve the problem, along with the adhoc Weiszfeld method, see "Sur le point pour lequel la Somme des distances de n points donnes est minimum", by Weiszfeld, Tohoku Mathematical Journal, First Series, 43, pg. 355-386, 1937 or "On the point for which the sum of the distances to n given points is minimum", by E. Weiszfeld and F. Plastria, Annals of Operations Research, 167, pg. 7-41, 2009. <DOI:10.1007/s10479-008-0352-z>.