Implements a web-based graphics device for animated visualisations.
  Modelled on the 'base' syntax, it extends the 'base' graphics functions to
  support frame-by-frame animation and keyframes animation.
  The target use cases are real-time animated visualisations, including agent-based
  models, dynamical systems, and animated diagrams.
  The generated visualisations can be deployed as GIF images / MP4 videos, as
  'Shiny' apps (with interactivity) or as HTML documents through embedding into
  R Markdown documents.

Provides functions for animations in statistics, covering topics
    in probability theory, mathematical statistics, multivariate statistics,
    non-parametric statistics, sampling survey, linear models, time series,
    computational statistics, data mining and machine learning. These functions
    may be helpful in teaching statistics and data analysis. Also provided in this
    package are a series of functions to save animations to various formats, e.g.
    Flash, 'GIF', HTML pages, 'PDF' and videos. 'PDF' animations can be inserted
    into 'Sweave' / 'knitr' easily.

Create an interactive visualization to be used for communication purposes. Providing the function for preparing, plotting, and animating the data.

Functions are provided for defining animated,
 interactive data visualizations in R code, and rendering
 on a web page. The 2018 Journal of Computational and 
 Graphical Statistics paper,
 <doi:10.1080/10618600.2018.1513367>
 describes the concepts implemented.

Functions required to classify subjects within camera trap field data. The package can handle both images and videos. The authors recommend a two-step approach using Microsoft's 'MegaDector' model and then a second model trained on the classes of interest.

Animation of observed trajectories using spline-based interpolation (see for example, Buderman, F. E., Hooten, M. B., Ivan, J. S. and Shenk, T. M. (2016), <doi:10.1111/2041-210X.12465> "A functional model for characterizing long-distance movement behaviour". Methods Ecol Evol). Intended to be used exploratory data analysis, and perhaps for preparation of presentations.