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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "wnpmle" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'wnpmle: Weighted NPMLE for Recurrent Events with a Competing Terminal Event'
version: 0.1.2
abstract: '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) <https://doi.org/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) <https://doi.org/10.17615/pt0g-y207> and the transformation
  model framework of Zeng and Lin (2006) <https://doi.org/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) <https://doi.org/10.1080/01621459.2017.1401540>.'
authors:
- family-names: Bellach
  given-names: Anna
  email: abellach.biostat@gmail.com
repository: https://cran.r-universe.dev
repository-code: https://github.com/abellach/wnpmle
commit: c493d08e09659e5a7857bfd9e646e1bb08df740a
url: https://github.com/abellach/wnpmle
date-released: '2026-06-18'
contact:
- family-names: Bellach
  given-names: Anna
  email: abellach.biostat@gmail.com