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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.3.0 |
rolling linux/jammy R-4.5 | exposureEM_0.3.0.tar.gz |
128.5 KiB |
0.3.0 |
rolling linux/noble R-4.5 | exposureEM_0.3.0.tar.gz |
128.4 KiB |
0.3.0 |
rolling source/ R- | exposureEM_0.3.0.tar.gz |
46.9 KiB |
0.3.0 |
latest linux/jammy R-4.5 | exposureEM_0.3.0.tar.gz |
128.5 KiB |
0.3.0 |
latest linux/noble R-4.5 | exposureEM_0.3.0.tar.gz |
128.4 KiB |
0.3.0 |
latest source/ R- | exposureEM_0.3.0.tar.gz |
46.9 KiB |
0.3.0 |
2026-04-23 source/ R- | exposureEM_0.3.0.tar.gz |
0 B |