Functions and data sets for reproducing selected results from
  the book "Quantitative Risk Management: Concepts, Techniques and Tools".
  Furthermore, new developments and auxiliary functions for Quantitative
  Risk Management practice.

Functionality for generating (randomized) quasi-random numbers in
  high dimensions.

Quantile regression (QR) for Nonlinear
             Mixed-Effects Models via the asymmetric Laplace distribution (ALD). 
             It uses the Stochastic Approximation of the EM (SAEM) algorithm for 
             deriving exact maximum likelihood estimates and full inference result
             is 
             for the fixed-effects and variance components.
             It also provides prediction and graphical summaries for assessing the algorithm
             convergence and fitting results.

Fit quantile regression neural network models with optional
    left censoring, partial monotonicity constraints, generalized additive
    model constraints, and the ability to fit multiple non-crossing quantile
    functions following Cannon (2011) <doi:10.1016/j.cageo.2010.07.005>
    and Cannon (2018) <doi:10.1007/s00477-018-1573-6>.

Execute multi-step 'SQL' workflows by
    leveraging specially formatted comments to define and control
    execution. This enables users to mix queries, commands, and metadata
    within a single script. Results are returned as named objects for use
    in downstream workflows.

Streamlines and accelerates the process of saving and loading R objects, improving speed and compression compared to other methods. The package provides two compression formats: the 'qs2' format, which uses R serialization via the C API while optimizing compression and disk I/O, and the 'qdata' format, featuring custom serialization for slightly faster performance and better compression. Additionally, the 'qs2' format can be directly converted to the standard 'RDS' format, ensuring long-term compatibility with future versions of R.

Molecular descriptors and outcomes for several public domain data sets