Provides direct access to linked names for the same entity across the world's major name authority files, including national and regional variations in language, character set, and spelling. For more information go to <https://viaf.org/>.

The Variable Infiltration Capacity (VIC) model is a macroscale
    hydrologic model that solves full water and energy balances, originally
    developed by Xu Liang at the University of Washington (UW).
    The version of VIC source code used is of 5.0.1 on <https://github.com/UW-Hydro/VIC/>,
    see Hamman et al. (2018).
    Development and maintenance of the current official version
    of the VIC model at present is led by the UW Hydro (Computational Hydrology
    group) in the Department of Civil and Environmental Engineering at UW. VIC is
    a research model and in its various forms it has been applied to most of the
    major river basins around the world, as well as globally 
    <http://vic.readthedocs.io/en/master/Documentation/References/>. 
    References: "Liang, X., D. P. Lettenmaier, E. F. Wood, and
    S. J. Burges (1994), A simple hydrologically based model of land surface water
    and energy fluxes for general circulation models, J. Geophys. Res., 99(D7),
    14415-14428, <doi:10.1029/94JD00483>"; 
    "Hamman, J. J., Nijssen, B., Bohn, T. J., Gergel, D. R., and Mao, Y. (2018), The
    Variable Infiltration Capacity model version 5 (VIC-5): infrastructure improvements
    for new applications and reproducibility, Geosci. Model Dev., 11, 3481-3496, 
    <doi:10.5194/gmd-11-3481-2018>".

Compute group-specific intraclass correlation coefficients, 
    Bayesian testing of homogenous within-group variance, and spike-and-slab
    model selection to determine which groups share a common within-group 
    variance in a one-way random effects model <10.31234/osf.io/hpq7w>.

A shiny app for accurate estimation of vaccine induced immunogenicity 
    with bivariate linear modeling. Method is detailed in: Lhomme, Hejblum, Lacabaratz, 
    Wiedemann, Lelievre, Levy, Thiebaut & Richert (2020). Journal of Immunological Methods, 
    477:112711. <doi:10.1016/j.jim.2019.112711>.