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.

The time series forecasting framework for use with the 'tidymodels' ecosystem. 
    Models include ARIMA, Exponential Smoothing, and additional time series models
    from the 'forecast' and 'prophet' packages. Refer to "Forecasting Principles & Practice, Second edition" 
    (<https://otexts.com/fpp2/>).
    Refer to "Prophet: forecasting at scale" 
    (<https://research.facebook.com/blog/2017/02/prophet-forecasting-at-scale/>.).

A 'modeltime' extension that implements forecast resampling tools
    that assess time-based model performance and stability for a single time series, 
    panel data, and cross-sectional time series analysis.

A collection of tools to deal with statistical models. 
  The functionality is experimental and the user interface is likely to
  change in the future. The documentation is rather terse, but packages `coin'
  and `party' have some working examples. However, if you find the
  implemented ideas interesting we would be very interested in a discussion
  of this proposal. Contributions are more than welcome!

Makes a word cloud of text, sized by the frequency of the word, and colored either by user-specified colors or colored by the strength of the coefficient of that text derived from a regression model.