PPMiss
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) <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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.2 |
rolling linux/jammy R-4.5 | PPMiss_0.1.2.tar.gz |
43.7 KiB |
0.1.2 |
rolling linux/noble R-4.5 | PPMiss_0.1.2.tar.gz |
43.6 KiB |
0.1.2 |
rolling source/ R- | PPMiss_0.1.2.tar.gz |
10.5 KiB |
0.1.2 |
latest linux/jammy R-4.5 | PPMiss_0.1.2.tar.gz |
43.7 KiB |
0.1.2 |
latest linux/noble R-4.5 | PPMiss_0.1.2.tar.gz |
43.6 KiB |
0.1.2 |
latest source/ R- | PPMiss_0.1.2.tar.gz |
10.5 KiB |
0.1.2 |
2026-04-26 source/ R- | PPMiss_0.1.2.tar.gz |
10.5 KiB |
0.1.2 |
2026-04-23 source/ R- | PPMiss_0.1.2.tar.gz |
10.5 KiB |
0.1.2 |
2026-04-09 windows/windows R-4.5 | PPMiss_0.1.2.zip |
50.0 KiB |
0.1.1 |
2025-04-20 source/ R- | PPMiss_0.1.1.tar.gz |
11.0 KiB |