Visualisation of multidimensional data through different Andrews curves: 
   Andrews, D. F. (1972) Plots of High-Dimensional Data. Biometrics, 28(1), 125-136. <doi:10.2307/2528964>.

Storing very large data objects on a local drive, while still making it possible to manipulate the data in an efficient manner.

Provides a comprehensive system for selecting
    variables and weighting data to match the specifications of the American
    National Election Studies. The package includes methods for identifying
    discrepant variables, raking data, and assessing the effects of the raking
    algorithm. It also allows automated re-raking if target variables fall
    outside identified bounds and allows greater user specification than other
    available raking algorithms. A variety of simple weighted statistics that
    were previously in this package (version .55 and earlier) have been moved to
    the package 'weights.'

Simulate an angler population, sample the simulated population with a user-specified survey times, and calculate metrics from a bus route-type creel survey.

Opens and imports log files from Angstrom Engineering Thermal Evaporator
    and extracts basic characteristics, such as base pressure, time of the evaporation. 
    It can visualize the deposition observables for review.

Helper functions for working with Regional Ocean Modeling System 'ROMS' output. See
    <https://www.myroms.org/> for more information about 'ROMS'.

Provides: (1) Tools to infer dominance hierarchies based on calculating Elo scores, but with custom functions to improve estimates in animals with relatively stable dominance ranks. (2) Tools to plot the shape of the dominance hierarchy and estimate the uncertainty of a given data set.

Simple animated versions of basic R plots, using the 'animation'
    package. Includes animated versions of plot, barplot, persp, contour,
    filled.contour, hist, curve, points, lines, text, symbols, segments, and
    arrows.

Synthetic generation of 1-D and 2-D correlated random walks (CRWs) for animal movement with behavioral switching, and particle filter estimation of movement parameters from observed trajectories using Extended Kalman Filter (EKF) model. See Ackerman (2018) <https://digital.library.temple.edu/digital/collection/p245801coll10/id/499150>.