Performs simple correspondence analysis on a two-way contingency table, 
    or multiple correspondence analysis (homogeneity analysis) 
    on data with p categorical variables,
    and produces bootstrap-based elliptical confidence regions around the 
    projected coordinates for the category points. 
    Includes routines to plot the results in a variety of styles. 
    Also reports the standard numerical output for correspondence analysis.

A set of functions to conduct Conjunctive Analysis of Case Configurations (CACC) as described in Miethe, Hart, and Regoeczi (2008) <doi:10.1007/s10940-008-9044-8>, and identify and quantify situational clustering in dominant case configurations as described in Hart (2019) <doi:10.1177/0011128719866123>. Initially conceived as an exploratory technique for multivariate analysis of categorical data, CACC has developed to include formal statistical tests that can be applied in a wide variety of contexts. This technique allows examining composite profiles of different units of analysis in an alternative way to variable-oriented methods.

Easily cache and retrieve computation results. The package works seamlessly across interactive R sessions, R scripts and Rmarkdown documents.

Key-value stores with automatic pruning. Caches can limit
    either their total size or the age of the oldest object (or both),
    automatically pruning objects to maintain the constraints.

A toolkit to perform cross-species analysis based on scRNA-seq data. This package contains 5 main features. (1) identify Markers in each cluster. (2) Cell type annotation (3) identify conserved markers. (4) identify conserved cell types. (5) identify conserved modules of regulatory networks.

Computes classification accuracy and consistency indices under Item Response Theory. Implements the total score IRT-based methods in Lee, Hanson & Brennen (2002) and Lee (2010), the IRT-based methods in Rudner (2001, 2005), and the total score nonparametric methods in Lathrop & Cheng (2014). For dichotomous and polytomous tests.