Estimate nonlinear vector autoregression models (also known as the 
    next generation reservoir computing) for nonlinear dynamic systems. The 
    algorithm was described by Gauthier et al. (2021) <doi:10.1038/s41467-021-25801-2>.

Fits Bayesian regularized varying coefficient models with the Nonparametric Varying Coefficient Spike-and-Slab Lasso (NVC-SSL) introduced by Bai et al. (2023) <https://jmlr.org/papers/volume24/20-1437/20-1437.pdf>. Functions to fit frequentist penalized varying coefficients are also provided, with the option of employing the group lasso penalty of Yuan and Lin (2006) <doi:10.1111/j.1467-9868.2005.00532.x>, the group minimax concave penalty (MCP) of Breheny and Huang <doi:10.1007/s11222-013-9424-2>, or the group smoothly clipped absolute deviation (SCAD) penalty of Breheny and Huang (2015) <doi:10.1007/s11222-013-9424-2>.

The n-vector framework uses the normal vector to
    the Earth ellipsoid (called n-vector) as a non-singular position
    representation that turns out to be very convenient for practical
    position calculations.  The n-vector is simple to use and gives exact
    answers for all global positions, and all distances, for both
    ellipsoidal and spherical Earth models.  This package is a translation
    of the 'Matlab' library from FFI, the Norwegian Defence Research
    Establishment, as described in Gade (2010)
    <doi:10.1017/S0373463309990415>.

Creates quasi-proportional Venn diagrams with an arbitrary number of sets.
            It is related to the old 'nVennR' package, but the algorithm and use have been reworked.

Functions for working with (grouped) multivariate normal variance mixture
  distributions (evaluation of distribution functions and densities,
  random number generation and parameter estimation), including
  Student's t distribution for non-integer degrees-of-freedom as well as the grouped t
  distribution and copula with multiple degrees-of-freedom parameters.
  See <doi:10.18637/jss.v102.i02> for a high-level description of select functionality.