https://abellach.r-universe.devRecent package updates in abellachR-universehttps://github.com/abellach.pnghttps://abellach.r-universe.devTue, 09 Jun 2026 03:31:03 GMTabellach.biostat@gmail.com (Anna Bellach)Provides regression modeling and prediction for the marginal mean of recurrent events in the presence of a competing terminal event based on the weighted nonparametric maximum likelihood estimator (wNPMLE) of Bellach and Kosorok (2026) <https://arxiv.org/abs/2605.25934>. Two large classes of transformation models are included: the Box-Cox transformation models and the logarithmic transformation models, extending the proportional means model of Ghosh and Lin (2002) <doi:10.17615/pt0g-y207> and the model of Zeng and Lin (2006) <doi:10.1093/biomet/93.3.627>. Parameter estimates are derived via automatic differentiation using the Template Model Builder (TMB) framework. Standard errors are computed via a sandwich variance estimator with correction for the estimated weights, following Bellach, Kosorok, Ruschendorf and Fine (2019) <doi:10.1080/01621459.2017.1401540>.https://github.com/r-universe/abellach/actions/runs/27817252275Tue, 09 Jun 2026 03:31:03 GMTwnpmle0.1.1successhttps://abellach.r-universe.devhttps://github.com/abellach/wnpmlewnpmle.Rmdwnpmle.htmlGetting Started with wnpmle2026-06-03 17:50:522026-06-08 22:53:24