wnpmle: Weighted NPMLE for Recurrent Events with a Competing Terminal
Event
Provides regression modeling and prediction for the marginal
mean of recurrent events in the presence of a competing terminal event
using the weighted nonparametric maximum likelihood estimator (wNPMLE)
of Bellach and Kosorok (2026)
<doi:10.48550/arXiv.2605.25934>. Two classes of transformation
models are implemented: Box-Cox transformation models and logarithmic
transformation models. These extend the proportional means model of
Ghosh and Lin (2002) <doi:10.17615/pt0g-y207> and the transformation
model framework of Zeng and Lin (2006)
<doi:10.1093/biomet/93.3.627>. Parameter estimation is performed using
automatic differentiation through the Template Model Builder (TMB)
framework. Standard errors are computed using sandwich variance
estimators that account for estimation of the inverse-probability
censoring weights following Bellach, Kosorok, Rüschendorf and Fine
(2019) <doi:10.1080/01621459.2017.1401540>.
| Version: |
0.1.3 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
TMB (≥ 1.9.0), survival, methods, MASS, graphics, grDevices, tools, utils |
| Suggests: |
testthat (≥ 3.0.0), knitr, rmarkdown |
| Published: |
2026-10-08 |
| DOI: |
10.32614/CRAN.package.wnpmle |
| Author: |
Anna Bellach [aut, cre] |
| Maintainer: |
Anna Bellach <abellach.biostat at gmail.com> |
| BugReports: |
https://github.com/abellach/wnpmle/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://github.com/abellach/wnpmle |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| CRAN checks: |
wnpmle results |
Documentation:
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