Progressive Regularized Vine Copula for Masked Competing Risks

Implements Progressive Regularized Vine Copula (Prog-Vine) frameworks for high-dimensional dependent competing risks with masked failure causes under Progressive Type-II Censoring. Fits Weibull marginals, estimates pair-copula trees using Expectation-Maximization (EM) algorithms, computes Louis observed information confidence intervals, and implements Data Augmentation Gibbs Samplers for Bayesian credible intervals.


Reference manual

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install.packages("ProgVine")

0.1.0 by Okechukwu J. Obulezi, 2 months ago


Browse source code at https://github.com/cran/ProgVine


Authors: Okechukwu J. Obulezi [aut, cre]


Documentation:   PDF Manual  


GPL-3 license


Imports stats


See at CRAN