Functions to allow users to build and analyze design consistent 
    tree and random forest models using survey data from a complex sample 
    design.  The tree model algorithm can fit a linear model to survey data 
    in each node obtained by recursively partitioning the data.  The splitting 
    variables and selected splits are obtained using a randomized permutation 
    test procedure which adjusted for complex sample design features used to 
    obtain the data. Likewise the model fitting algorithm produces 
    design-consistent coefficients to any specified least squares linear model 
    between the dependent and independent variables used in the end nodes.
    The main functions return the resulting binary tree or random forest as 
    an object of "rpms" or "rpms_forest" type. The package also provides methods
    modeling a "boosted" tree or forest model and a tree model for zero-inflated
    data as well as a number of functions and methods available for use with 
    these object types.

A set of functions to analyze and print the development of a
    commodity using the Point and Figure (P&F) approach. A P&F processor can be used
    to calculate daily statistics for the time series. These statistics can be used
    for deeper investigations as well as to create plots. Plots can be generated as
    well known X/O Plots in plain text format, and additionally in a more graphical
    format.

Wrapper for the 'PoetryDB' API <http://poetrydb.org> that allows for interaction and data extraction from the 
  database in an R interface. The 'PoetryDB' API is a database of poetry and poets implemented with 'MongoDB' to 
  enable developers and poets to easily access one of the most comprehensive poetry databases currently available.

Visualizations to explain the results of a topological
  data analysis. The goal of topological data analysis is to identify
  persistent topological structures, such as loops (topological circles)
  and voids (topological spheres), in data sets. The output of an
  analysis using the 'TDA' package is a Rips diagram (named after the
  mathematician Eliyahu Rips). The goal of 'RPointCloud' is to fill in
  these holes in the data by providing tools to visualize the features
  that help explain the structures found in the Rips diagram. See McGee
  and colleagues (2024) <doi:10.1101/2024.05.16.593927>.