Creating alluvial diagrams (also known as parallel sets plots) for multivariate
  and time series-like data.

Provides tools for defining recurrence rules and recurrence
    sets. Recurrence rules are a programmatic way to define a recurring
    event, like the first Monday of December. Multiple recurrence rules
    can be combined into larger recurrence sets. A full holiday and
    calendar interface is also provided that can generate holidays within
    a particular year, can detect if a date is a holiday, can respect
    holiday observance rules, and allows for custom holidays.

A collection of datasets on the Alone survival TV series in tidy format. 
  Included in the package are 4 datasets detailing the survivors, their loadouts,
  episode details and season information.

A collection of tools that support data splitting, predictive modeling, and model evaluation. 
    A typical function is to split a dataset into a training dataset and a test dataset. 
    Then compare the data distribution of the two datasets.
    Another feature is to support the development of predictive models and to compare the performance of several predictive models, 
    helping to select the best model.

Creates all leave-one-out models and produces predictions for test samples.

Provides a routine to partial out factors with many levels during the optimization of the log-likelihood function of the corresponding generalized linear model (glm). The package is based on the algorithm described in Stammann (2018) <arXiv:1707.01815> and is restricted to glm's that are based on maximum likelihood estimation and nonlinear. It also offers an efficient algorithm to recover estimates of the fixed effects in a post-estimation routine and includes robust and multi-way clustered standard errors. Further the package provides analytical bias corrections for binary choice models derived by Fernandez-Val and Weidner (2016) <doi:10.1016/j.jeconom.2015.12.014> and Hinz, Stammann, and Wanner (2020) <arXiv:2004.12655>.