Draws tornado plots for model sensitivity to univariate changes.  Implements methods for many modeling methods including linear models, generalized linear models, survival regression models, and arbitrary machine learning models in the caret package.  Also draws variable importance plots.

A framework for statistical analysis in content analysis. In addition to a pipeline for preprocessing text corpora and linking to the latent Dirichlet allocation from the 'lda' package, plots are offered for the descriptive analysis of text corpora and topic models. In addition, an implementation of Chang's intruder words and intruder topics is provided. Sample data for the vignette is included in the toscaData package, which is available on gitHub: <https://github.com/Docma-TU/toscaData>.

Operators and functions provided by base R sometimes lack some
    features found in other programming languages, such as the ability to
    concatenate strings using + or to repeat strings using *. This package aims
    at providing such functionality without breaking existing code, i.e., only
    statements, that would throw errors in pure base R are patched.

Base R sometimes requires verbose statements for simple,
    often recurring tasks, such as printing text without trailing
    space, ending with newline. This package aims at providing
    shorthands for such tasks.

A general framework of two directional simultaneous inference
    is provided for high-dimensional as well as the fixed dimensional models with manifest
    variable or latent variable structure, such as high-dimensional mean models, high-
    dimensional sparse regression models, and high-dimensional latent factors models.
    It is making the simultaneous inference on a set of parameters from two directions,
    one is testing whether the estimated zero parameters indeed are zero and the other is
    testing whether there exists zero in the parameter set of non-zero. More details can be 
    referred to Wei Liu, et al. (2022) <doi:10.48550/arXiv.2012.11100>.