bootComb:Combine Parameter Estimates via Parametric Bootstrap
Propagate uncertainty from several estimates when combining these estimates via a function. This is done by using
the parametric bootstrap to simulate values from the
distribution of each estimate to build up an empirical
distribution of the combined parameter. Finally either the
percentile method is used or the highest density interval is
chosen to derive a confidence interval for the combined
parameter with the desired coverage. Gaussian copulas are used
for when parameters are assumed to be dependent / correlated.
References: Davison and Hinkley (1997,ISBN:0-521-57471-4) for
the parametric bootstrap and percentile method, Gelman et al.
(2014,ISBN:978-1-4398-4095-5) for the highest density interval,
Stockdale et al. (2020)<doi:10.1016/j.jhep.2020.04.008> for an
example of combining conditional prevalences.
