Implements two-mode clustering (biclustering) using 
    genetic algorithms. The method was first introduced in 
    Hageman et al. (2008) <doi:10.1007/s11306-008-0105-7>. The 
    package provides tools for fitting, visualization, and 
    validation of two-mode cluster structures in data matrices.

Fit two-part regression models for zero-inflated data. The models and their components are represented using S4 classes and methods. Average Marginal effects and predictive margins with standard errors and
  confidence intervals can be calculated from two-part model objects. Belotti, F., Deb, P., Manning, W. G., & Norton, E. C. (2015) <doi:10.1177/1536867X1501500102>.

Density, distribution function, quantile function, 
    and random generation function, maximum likelihood estimation (MLE), 
    penalized maximum likelihood estimation (PMLE), the quartiles method estimation (QM),
    and median rank estimation (MEDRANK) for the two-parameter exponential distribution.
    MLE and PMLE are based on Mengjie Zheng (2013)<https://scse.d.umn.edu/sites/scse.d.umn.edu/files/mengjie-thesis_masters-1.pdf>.
    QM is based on Entisar Elgmati and Nadia Gregni (2016)<doi:10.5539/ijsp.v5n5p12>.
    MEDRANK is based on Matthew Reid (2022)<doi:10.5281/ZENODO.3938000>.

Tools for constructing and analyzing two-phase experimental designs under correlated error structures. Version 1.1.1 includes improved efficiency factor classification with tolerance control, updated plot visualizations, and improved clarity of the results. The conceptual framework and the term two-phase were introduced by McIntyre (1955) <doi:10.2307/3001770>).

Facilitates development and application of two-regression
    algorithms for research-grade wearable devices. It provides an easy
    way for users to access previously-developed algorithms, and also to
    develop their own. Initial motivation came from Hibbing PR, LaMunion SR,
    Kaplan AS, & Crouter SE (2018) <doi:10.1249/MSS.0000000000001532>.
    However, other algorithms are now supported. Please see the associated
    references in the package documentation for full details of the algorithms
    that are supported.