Copula-Based Estimator for Long-Range Dependent Processes under Missing Data R package PPMiss version 0.1.2 Implements the copula-based estimator for univariate long-range dependent processes, introduced in Pumi et al. (2023) <doi:10.1007/s00362-023-01418-z>. Notably, this estimator is capable of handling missing data and has been shown to perform exceptionally well, even when up to 70% of data is missing (as reported in <doi:10.48550/arXiv.2303.04754>) and has been found to outperform several other commonly applied estimators. Software Depends: R (>= 4.0.0) Imports: copula, pracma, stats, zoo Taiane Schaedler Prass <taianeprass@gmail.com> Comprehensive R Archive Network (CRAN) Taiane Schaedler Prass [aut, cre, com] (ORCID: <https://orcid.org/0000-0003-3136-909X>), Guilherme Pumi [aut, ctb] (ORCID: <https://orcid.org/0000-0002-6256-3170>) GPL (>= 3) 2026-02-18 application/tgz https://CRAN.R-project.org/package=PPMiss doi:10.32614/CRAN.package.PPMiss