Based on 'STATA' xtsum command, it is used to compute summary statistics for a panel data set. It generates overall, between-group, and within-group statistics for specified variables in a panel data set, as presented in S. Porter (2023) <https://stephenporter.org/files/xtsum_handout.pdf>, StataCorp (2023) <https://www.stata.com/manuals/xtxtsum.pdf>.

Extends standard penalized regression (Lasso, Ridge, and Elastic-net) to allow feature-specific shrinkage based on external information with the goal of achieving a better prediction accuracy and variable selection. Examples of external information include the grouping of predictors, prior knowledge of biological importance, external p-values, function annotations, etc. The choice of multiple tuning parameters is done using an Empirical Bayes approach. A majorization-minimization algorithm is employed for implementation.

This is a collection of some useful functions when dealing with text data. 
    Currently it only contains a very efficient function of decoding HTML entities
    in character vectors by 'Rcpp' routine.

Calculates a number of valuation adjustments including CVA, DVA,
    FBA, FCA, MVA and KVA. A two-way margin agreement has been implemented. For
    the KVA calculation four regulatory frameworks are supported: CEM, (simplified) SA-CCR, OEM
	and IMM. The probability of default is implied through the credit spreads curve.
    The package supports an exposure calculation based on SA-CCR which includes several trade types
    and a simulated path which is currently available only for Interest Rate Swaps. The latest regulatory capital charge methodologies
    have been implementing including BA-CVA & SA-CVA.

Provides tools for reading, parsing and visualizing simulation data stored in 'xvg'/'xpm' file
  formats (commonly generated by 'GROMACS' molecular dynamics software). Streamlines post-processing
  and analysis of molecular dynamics ('MD') simulation outputs, enabling efficient exploration of
  molecular stability and conformational changes. Supports import of trajectory metrics ('RMSD',
  energy, temperature) and creation of publication-ready visualizations through integration with
  'ggplot2'.