Provides a calculator for the two-dimensional clinical Disease Activity 
    index for Psoriatic Arthritis (TwoDcDAPSA), a principal component-derived measure 
    that complements the conventional clinical DAPSA score. The TwoDcDAPSA captures 
    residual variation in patient-reported outcomes (pain and patient global assessment) 
    and joint counts (swollen and tender) after adjusting for standardized cDAPSA using 
    natural spline coefficients derived from published models. Residuals are 
    standardized and combined with fixed principal component loadings to yield a 
    continuous PROs-Joint Contrast (PJC) score and quartile groupings. The package 
    applies pre-specified coefficients and loadings to new datasets but does not 
    estimate spline models or principal components itself.

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>.