Provides functionality for working with tensors, alternating
           forms, wedge products, Stokes's theorem, and related concepts
	   from the exterior calculus.   Uses 'disordR' discipline
	   (Hankin, 2022, <doi:10.48550/ARXIV.2210.03856>).  The
	   canonical reference would be M. Spivak
	   (1965, ISBN:0-8053-9021-9) "Calculus on Manifolds".  To cite
	   the package in publications please use Hankin (2022)
           <doi:10.48550/ARXIV.2210.17008>.

Trajectory data formed by human or animal movement is often marked 
    by periods of movement interspersed with periods of standing still. It is
    often of interest to researchers to separate geolocation trajectories of
    latitude/longitude points by clustering consecutive locations to produce a
    model of this behavior. This package implements the Stay Point detection
    algorithm originally described in Ye (2009) <doi:10.1109/MDM.2009.11> that
    uses time and distance thresholds to characterize spatial regions as
    'stops'. This package also implements the concept of merging described in
    Montoliu (2013) <doi:10.1007/s11042-011-0982-z> as stay point region
    estimation, which allows for clustering of temporally adjacent stops for
    which distance between the midpoints is less than the provided threshold.
    GPS-like data from various sources can be used, but the temporal thresholds
    must be considered with respect to the sampling interval, and the spatial 
    thresholds must be considered with respect to the measurement error.

Implements variable selection procedures for low to moderate size generalized linear regressions models. It includes the STOPES functions for linear regression (Capanu M, Giurcanu M, Begg C, Gonen M, Optimized variable selection via repeated data splitting, Statistics in Medicine, 2020, 19(6):2167-2184) as well as subsampling based optimization methods for generalized linear regression models (Marinela Capanu, Mihai Giurcanu, Colin B Begg, Mithat Gonen, Subsampling based variable selection for generalized linear models).