Hospitals, hospital systems, and even trauma systems that
    provide care to injured patients may not be aware of robust metrics
    that can help gauge the efficacy of their programs in saving the lives
    of injured patients.  'traumar' provides robust functions driven by
    the academic literature to automate the calculation of relevant
    metrics to individuals desiring to measure the performance of their
    trauma center or even a trauma system.  'traumar' also provides some
    helper functions for the data analysis journey. Users can refer to the
    following publications for descriptions of the methods used in
    'traumar'.  TRISS methodology, including probability of survival, and
    the W, M, and Z Scores - Flora (1978)
    <doi:10.1097/00005373-197810000-00003>, Boyd et al. (1987,
    PMID:3106646), Llullaku et al. (2009) <doi:10.1186/1749-7922-4-2>,
    Singh et al. (2011) <doi:10.4103/0974-2700.86626>, Baker et al. (1974,
    PMID:4814394), and Champion et al. (1989)
    <doi:10.1097/00005373-198905000-00017>. For the Relative Mortality
    Metric, see Napoli et al. (2017) <doi:10.1080/24725579.2017.1325948>,
    Schroeder et al. (2019) <doi:10.1080/10903127.2018.1489021>, and
    Kassar et al. (2016) <doi:10.1177/00031348221093563>. For more
    information about methods to calculate over- and under-triage in
    trauma hospital populations and samples, please see the following
    publications - Peng & Xiang (2016) <doi:10.1016/j.ajem.2016.08.061>,
    Beam et al. (2022) <doi:10.23937/2474-3674/1510136>, Roden-Foreman et
    al. (2017) <doi:10.1097/JTN.0000000000000283>.

'Travel Time' API <https://docs.traveltime.com/api/overview/introduction> helps users find locations by journey time rather than using ‘as the crow flies’ distance.
  Time-based searching gives users more opportunities for personalisation and delivers a more relevant search.

Contains R functions for simulating and estimating integer-valued trawl processes as 
    described in the article Veraart (2019),"Modeling, simulation and inference for
    multivariate time series of counts using trawl processes", Journal of Multivariate Analysis,
    169, pages 110-129,
    <doi:10.1016/j.jmva.2018.08.012> and for 
    simulating random vectors from the bivariate negative binomial and the bi- and trivariate 
    logarithmic series distributions.