A lightweight vector database for text retrieval in R with embedded
    machine learning models and no external API (Application Programming
    Interface) keys. Supports dense and hybrid search, optional HNSW
    (Hierarchical Navigable Small World) approximate nearest-neighbor indexing,
    faceted filters with ACL (Access Control List) metadata, command-line
    tools, and a local dashboard built with 'shiny'. The HNSW method is
    described by Malkov and Yashunin (2018) <doi:10.1109/TPAMI.2018.2889473>.

Mixed type vectors are useful for combining semantically similar 
  classes. Some examples of semantically related classes include time across 
  different granularities (e.g. daily, monthly, annual) and probability 
  distributions (e.g. Normal, Uniform, Poisson). These groups of vector types 
  typically share common statistical operations which vary in results with the 
  attributes of each vector. The 'vecvec' data structure facilitates efficient 
  storage and computation across multiple vectors within the same object.

Provides platform for Vedic calendar system having several
    functionalities to facilitate conversion between Gregorian and Vedic
    calendar systems, and helpful in examining its impact in the
    time series analysis domain.

Implements the Variable importance Explainable Elastic Shape Analysis pipeline for explainable machine learning with functional data inputs. Converts training and testing data functional inputs to elastic shape analysis principal components that account for vertical and/or horizontal variability. Computes feature importance to identify important principal components and visualizes variability captured by functional principal components. See Goode et al. (2025) <doi:10.48550/arXiv.2501.07602> for technical details about the methodology.

The 'Vega-Lite' 'JavaScript' framework provides a higher-level grammar
    for visual analysis, akin to 'ggplot' or 'Tableau', that generates complete 'Vega'
    specifications. Functions exist which enable building a valid 'spec' from scratch
    or importing a previously created 'spec' file. Functions also exist to export 'spec'
    files and to generate code which will enable plots to be embedded in properly
    configured web pages. The default behavior is to generate an 'htmlwidget'.