Copula-Based Estimator for Long-Range Dependent Processes under Missing Data

Implements the copula-based estimator for univariate long-range dependent processes, introduced in Pumi et al. (2023) . 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 ) and has been found to outperform several other commonly applied estimators.