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.
| Version: | 0.1.1 |
| Depends: | R (≥ 4.0.0) |
| Imports: | copula, pracma, stats, zoo |
| Published: | 2023-09-04 |
| DOI: | 10.32614/CRAN.package.PPMiss |
| Author: | Taiane Schaedler Prass
 [aut, cre,
com],
Guilherme Pumi
[aut, ctb] |
| Maintainer: | Taiane Schaedler Prass <taianeprass at gmail.com> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | yes |
| Materials: | NEWS |
| CRAN checks: | PPMiss results |
Documentation:
| Reference manual: | PPMiss.pdf |
Downloads:
| Package source: | PPMiss_0.1.1.tar.gz |
| Windows binaries: | r-devel: PPMiss_0.1.1.zip, r-release: PPMiss_0.1.1.zip, r-oldrel: PPMiss_0.1.1.zip |
| macOS binaries: | r-release (arm64): PPMiss_0.1.1.tgz, r-oldrel (arm64): PPMiss_0.1.1.tgz, r-release (x86_64): PPMiss_0.1.1.tgz, r-oldrel (x86_64): PPMiss_0.1.1.tgz |
| Old sources: | PPMiss archive |
Linking:
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