Create beautifully color-coordinated and customized themes
    for your 'xaringan' slides, without writing any CSS. Complete your
    slide theme with 'ggplot2' themes that match the font and colors used
    in your slides.  Customized styles can be created directly in your
    slides' 'R Markdown' source file or in a separate external script.

Functions to extract business financial information from
  an Extensible Business Reporting Language ('XBRL') instance file and the
  associated collection of files that defines its 'Discoverable' Taxonomy
  Set ('DTS').

Functions for Estimating a (c)DCC-GARCH Model in large dimensions
    based on a publication by Engle et,al (2017) <doi:10.1080/07350015.2017.1345683> and Nakagawa et,al (2018) <doi:10.3390/ijfs6020052>.
    This estimation method is consist of composite likelihood method by Pakel et al. (2014) <http://paneldataconference2015.ceu.hu/Program/Cavit-Pakel.pdf>
    and (Non-)linear shrinkage estimation of covariance matrices by Ledoit and Wolf (2004,2015,2016). (<doi:10.1016/S0047-259X(03)00096-4>,
    <doi:10.1214/12-AOS989>, <doi:10.1016/j.jmva.2015.04.006>).

Miscellaneous functions used for x-engineering (feature engineering) or 
  for supporting in other packages maintained by 'Shichen Xie'.

Implementation of a scalable, highly configurable, and 
        e(x)tended architecture for (e)volutionary and (g)enetic (a)lgorithms.
        Multiple representations (binary, real-coded, permutation, and 
        derivation-tree), a rich collection of genetic operators, 
        as well as an extended processing pipeline are provided 
        for genetic algorithms (Goldberg, D. E. (1989, ISBN:0-201-15767-5)),
        differential evolution (Price, Kenneth V., Storn, Rainer M. and Lampinen, Jouni A. (2005)
        <doi:10.1007/3-540-31306-0>), simulated annealing (Aarts, E., and Korst, J.
        (1989, ISBN:0-471-92146-7)), grammar-based genetic programming 
        (Geyer-Schulz (1997, ISBN:978-3-7908-0830-X)), and grammatical evolution 
        (Ryan, C., O'Neill, M., and Collins, J. J. (2018) <doi:10.1007/978-3-319-78717-6>).
        All algorithms reuse basic adaptive mechanisms for performance optimization.
        Sequential or parallel execution (on multi-core machines, 
        local clusters, and high performance computing environments) 
        is available for all algorithms. See 
        <https://github.com/ageyerschulz/xega/tree/main/examples/executionModel>.