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. 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.

Version: 1.0.0
Suggests: HDInterval (≥ 0.2.2)
Published: 2020-09-07
Author: Marc Henrion ORCID iD [aut, cre]
Maintainer: Marc Henrion <mhenrion at mlw.mw>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
CRAN checks: bootComb results

Downloads:

Reference manual: bootComb.pdf
Package source: bootComb_1.0.0.tar.gz
Windows binaries: r-devel: bootComb_1.0.0.zip, r-release: bootComb_1.0.0.zip, r-oldrel: bootComb_1.0.0.zip
macOS binaries: r-release: bootComb_1.0.0.tgz, r-oldrel: bootComb_1.0.0.tgz
Old sources: bootComb archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=bootComb to link to this page.