Computes the product moments of the truncated multivariate normal 
    distribution, particularly for cases involving patterned 
    variance-covariance matrices. It also has the capability to calculate these 
    moments with arbitrary positive-definite matrices, although performance may 
    degrade for high-dimensional variables.

Does local optimization using two derivatives and trust regions.
    Guaranteed to converge to local minimum of objective function.

Trusted Timestamps (tts) are created by incorporating a hash of a file or dataset into a transaction on the decentralized blockchain (Stellar network). 
    The package makes use of a free service provided by <https://stellarapi.io>.

Makes data wrangling with ID-related aspects more comfortable.
    Provides functions that make it easy to inspect various subject-generated ID codes (SGIC) for plausibility.
    Also helps with inspecting other common identifiers, ensuring that your data stays clean and reliable.

Trust region algorithm for nonlinear optimization. Efficient when
    the Hessian of the objective function is sparse (i.e., relatively few nonzero
    cross-partial derivatives). See Braun, M. (2014) <doi:10.18637/jss.v060.i04>.

Provides tools for evaluating the trustworthiness of machine
    learning models in production and research settings. Computes a
    Stability Index that quantifies the consistency of model predictions
    across multiple runs or resamples, and a Robustness Score that measures
    model resilience under small input perturbations. Designed for data
    scientists, ML engineers, and researchers who need to monitor and ensure
    model reliability, reproducibility, and deployment readiness.

Advanced tryCatch() and try() functions for better error handling
             (logging, stack trace with source code references and support for post-mortem analysis via dump files).

Differentiate client errors (4xx)
  from server errors (5xx) for the 'plumber' and 
  'RestRserve' HTTP API frameworks. The package
  also includes a built-in logging mechanism
  to standard output (STDOUT) or standard error
  (STDERR) depending on the log level.