Collection of miscellaneous utility functions, supporting data 
    transformation tasks like recoding, dichotomizing or grouping variables, 
    setting and replacing missing values. The data transformation functions 
    also support labelled data, and all integrate seamlessly into a 
    'tidyverse'-workflow.

Collection of plotting and table output functions for data
    visualization. Results of various statistical analyses (that are commonly used
    in social sciences) can be visualized using this package, including simple and
    cross tabulated frequencies, histograms, box plots, (generalized) linear models,
    mixed effects models, principal component analysis and correlation matrices, 
    cluster analyses, scatter plots, stacked scales, effects plots of regression 
    models (including interaction terms) and much more. This package supports
    labelled data.

A scalable method to estimate joint Species Distribution Models (jSDMs) for big community datasets based on a Monte Carlo approximation of the joint likelihood.  The numerical approximation is based on 'PyTorch' and 'reticulate', and can be run on CPUs and GPUs alike. The method is described in Pichler & Hartig (2021) <doi:10.1111/2041-210X.13687>. The package contains various extensions, including support for different response families, ability to account for spatial autocorrelation, and deep neural networks instead of the linear predictor in jSDMs.

Collection of convenient functions for common statistical computations,
             which are not directly provided by R's base or stats packages.
             This package aims at providing, first, shortcuts for statistical measures, 
             which otherwise could only be calculated with additional effort 
             (like Cramer's V, Phi, or effect size statistics like Eta or Omega squared), 
             or for which currently no functions available. Second, another focus 
             lies on weighted variants of common statistical measures and tests 
             like weighted standard error, mean, t-test, correlation, and more.