Comprehensive analytical tools are provided to characterize infectious disease superspreading from contact tracing surveillance data. The underlying theoretical frameworks of this toolkit include branching process with transmission heterogeneity (Lloyd-Smith et al. (2005) <doi:10.1038/nature04153>), case cluster size distribution (Nishiura et al. (2012) <doi:10.1016/j.jtbi.2011.10.039>, Blumberg et al. (2014) <doi:10.1371/journal.ppat.1004452>, and Kucharski and Althaus (2015) <doi:10.2807/1560-7917.ES2015.20.25.21167>), and decomposition of reproduction number (Zhao et al. (2022) <doi:10.1371/journal.pcbi.1010281>).

Automate the explanatory analysis of machine learning predictive 
    models. Generate advanced interactive model explanations in the form of 
    a serverless HTML site with only one line of code. This tool is 
    model-agnostic, therefore compatible with most of the black-box predictive
    models and frameworks. The main function computes various (instance and 
    model-level) explanations and produces a customisable dashboard, which 
    consists of multiple panels for plots with their short descriptions. It is 
    possible to easily save the dashboard and share it with others. modelStudio 
    facilitates the process of Interactive Explanatory Model Analysis introduced 
    in Baniecki et al. (2023) <doi:10.1007/s10618-023-00924-w>.

Create beautiful and customizable tables to summarize several
    statistical models side-by-side. Draw coefficient plots, multi-level
    cross-tabs, dataset summaries, balance tables (a.k.a. "Table 1s"), and
    correlation matrices. This package supports dozens of statistical models, and
    it can produce tables in HTML, LaTeX, Word, Markdown, PDF, PowerPoint, Excel,
    RTF, JPG, or PNG. Tables can easily be embedded in 'Rmarkdown' or 'knitr'
    dynamic documents. Details can be found in Arel-Bundock (2022)
    <doi:10.18637/jss.v103.i01>.

Provides a number of testthat tests that can be
    used to verify that tidy(), glance() and augment() methods meet
    consistent specifications. This allows methods for the same generic to
    be spread across multiple packages, since all of those packages can
    make the same guarantees to users about returned objects.