Split a dataframe, tibble, or data.table into training and test sets. Return either a list, an index, or directly assign training and test sets into memory.

A collection of commonly used tools for animal movement and other tracking 
 data. Variously distance, angle, bearing, distance-to, bearing-to and speed are 
 provided for geographic data that can be used directly or within 'tidyverse' 
 syntax. Distances and bearings are calculated using modern geodesic methods as 
 provided by Charles F. F. Karney (2013) <doi:10.1007/s00190-012-0578-z> 
 via the 'geographiclib' package.

Species trait data from many sources, including sequence data
    from NCBI (<https://www.ncbi.nlm.nih.gov/>), plant traits from BETYdb,
    and data from EOL Traitbank and BirdLife International.

Calculates trait moments from trait and community data using the 
  methods developed in Maitner et al (2021) <doi:10.22541/au.162196147.76797968/v1>.

Identifies clusters of individual longitudinal trajectories. In the spirit of Leffondre et al. (2004), the procedure involves identifying each trajectory to a point in the space of measures. In this context, a measure is a quantity meant to capture a certain characteristic feature of the trajectory. The points in the space of measures are then clustered using a version of the Spectral Clustering algorithm.

Classes and methods for trajectory data, with support for nesting individual Track objects in track sets (Tracks) and track sets for different entities in collections of Tracks. Methods include selection, generalization, aggregation, intersection, simulation, and plotting.

Estimation of group-based trajectory models, including finite mixture models for longitudinal data, 
    supporting censored normal, zero-inflated Poisson, logit, and beta distributions, 
    using expectation-maximization and quasi-Newton methods, with tools for model selection, 
    diagnostics, and visualization of latent trajectory groups,
    <doi:10.4159/9780674041318>, Nagin, D. (2005). Group-Based Modeling of Development. Cambridge, MA: Harvard University Press.
    and Noel (2022), <https://orbilu.uni.lu/>, thesis.