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) for an example of combining conditional prevalences.


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("bootComb")

1.1.1 by Marc Henrion, 24 days ago


Browse source code at https://github.com/cran/bootComb


Authors: Marc Henrion [aut, cre]


Documentation:   PDF Manual  


GPL-3 license


Imports MASS

Suggests HDInterval


See at CRAN