Contains functions for applying the horseshoe prior to high-
    dimensional linear regression, yielding the posterior mean and credible
    intervals, amongst other things. The key parameter tau can be equipped with
    a prior or estimated via maximum marginal likelihood estimation (MMLE).
    The main function, horseshoe, is for linear regression. In addition, there
    are functions specifically for the sparse normal means problem, allowing
    for faster computation of for example the posterior mean and posterior
    variance. Finally, there is a function available to perform variable
    selection, using either a form of thresholding, or credible intervals.

Provides the posterior estimates of the regression coefficients when horseshoe prior is specified. 
             The regression models considered here are logistic model for binary response and 
             log normal accelerated failure time model for right censored survival response. 
             The linear model analysis is also available for completeness. 
             All models provide deviance information criterion and widely applicable information criterion. 
             See <doi:10.1111/rssc.12377> Maity et. al. (2019) <doi:10.1111/biom.13132> Maity et. al. (2020).

Automatically displays the order and spatial weighting matrix of the distance between locations. This concept was derived from the research of Mubarak, Aslanargun, and Siklar (2021) <doi:10.52403/ijrr.20211150> and Mubarak, Aslanargun, and Siklar (2022) <doi:10.17654/0972361722052>. Distance data between locations can be imported from 'Ms. Excel', 'maps' package or created in 'R' programming directly. This package also provides 5 simulations of distances between locations derived from fictitious data, the 'maps' package, and from research by Mubarak, Aslanargun, and Siklar (2022) <doi:10.29244/ijsa.v6i1p90-100>.

Set of tools to help interested researchers to build hospital networks 
  from data on hospitalized patients transferred between hospitals. Methods provided 
  have been used in Donker T, Wallinga J, Grundmann H. (2010) <doi:10.1371/journal.pcbi.1000715>, 
  and Nekkab N, Crépey P, Astagneau P, Opatowski L, Temime L. (2020) <doi:10.1038/s41598-020-71212-6>.