Inference and dependence measure for the non-central squared Gaussian, Student, Clayton, Gumbel, and Frank copula models.The description of the methodology is taken from Section 3 of Nasri, Remillard and Bouezmarni (2019) <doi:10.1016/j.jmva.2019.03.007>.

Omics data come in different forms: gene expression, methylation, copy number, protein measurements and more.
    'NCutYX' allows clustering of variables, of samples, and both variables and samples (biclustering),
    while incorporating the dependencies across multiple types of Omics data.
    (SJ Teran Hidalgo et al (2017), <doi:10.1186/s12864-017-3990-1>).

Fits regularization paths for linear regression, GLM, and Cox
  regression models using lasso or nonconvex penalties, in particular the
  minimax concave penalty (MCP) and smoothly clipped absolute deviation (SCAD)
  penalty, with options for additional L2 penalties (the "elastic net" idea).
  Utilities for carrying out cross-validation as well as post-fitting
  visualization, summarization, inference, and prediction are also provided.
  For more information, see Breheny and Huang (2011) <doi:10.1214/10-AOAS388>
  or visit the ncvreg homepage <https://pbreheny.github.io/ncvreg/>.

Non-parametric dimensionality reduction function. Reduction with and without feature selection. Plot functions. Automated feature selections. Kosztyan et. al. (2024) <doi:10.1016/j.eswa.2023.121779>.

Streaming 'JSON' ('ndjson') has one 'JSON' record per-line
        and many modern 'ndjson' files contain large numbers of records.
        These constructs may not be columnar in nature, but it is often
        useful to read in these files and "flatten" the structure out to
        enable working with the data in an R 'data.frame'-like context.
        Functions are provided that make it possible to read in plain
        'ndjson' files or compressed ('gz') 'ndjson' files and either
        validate the format of the records or create "flat" 'data.table'
        structures from them.

Naive discriminative learning implements learning and
    classification models based on the Rescorla-Wagner equations and their
    equilibrium equations.