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exposureEM: Combined-Exposure Models by EM and Marquardt Optimization

Fits general two-component combined-exposure models for binary event histories when the event setting is not observed. The observed binary event is represented as the union of two latent component-specific binary events. Known exposure proportions enter as offsets. Parameters can be estimated by expectation-maximization, direct Marquardt-damped Newton-Raphson maximization of the observed likelihood, or a hybrid that uses several expectation-maximization iterations before direct optimization. Uncertainty is estimated with Louis' formula for the expectation-maximization estimator and the inverse observed Hessian for direct and hybrid fits. Complementary log-log, logit, and log component links are available for all three estimation methods.

Version: 0.3.0
Depends: R (≥ 4.1.0)
Imports: stats, utils
Published: 2026-09-21
DOI: 10.32614/CRAN.package.exposureEM
Author: Wenjing Meng [aut, cre]
Maintainer: Wenjing Meng <w2meng at ucsd.edu>
License: MIT + file LICENSE
NeedsCompilation: no
Citation: exposureEM citation info
Materials: README, NEWS
CRAN checks: exposureEM results

Documentation:

Reference manual: exposureEM.html , exposureEM.pdf

Downloads:

Package source: exposureEM_0.3.0.tar.gz
Windows binaries: r-devel: exposureEM_0.3.0.zip, r-release: not available, r-oldrel: exposureEM_0.3.0.zip
macOS binaries: r-release (arm64): exposureEM_0.3.0.tgz, r-oldrel (arm64): exposureEM_0.3.0.tgz, r-release (x86_64): exposureEM_0.3.0.tgz, r-oldrel (x86_64): exposureEM_0.3.0.tgz

Linking:

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

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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