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PPMiss
View on CRAN: Click
here
Download and install PPMiss package within the R console
Install from CRAN:
install.packages("PPMiss")
Install from Github:
library("remotes")
install_github("cran/PPMiss")
Install by package version:
library("remotes")
install_version("PPMiss", "0.1.1")
Attach the package and use:
library("PPMiss")
Maintained by
Taiane Schaedler Prass
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.PPMiss . PPMiss results . PPMiss.pdf . PPMiss_0.1.1.tar.gz . PPMiss_0.1.1.zip . PPMiss_0.1.1.zip . PPMiss_0.1.1.zip . PPMiss_0.1.1.tgz . PPMiss_0.1.1.tgz . PPMiss_0.1.1.tgz . PPMiss_0.1.1.tgz . PPMiss_0.1.1.tgz . PPMiss_0.1.1.tgz . PPMiss archive . https://CRAN.R-project.org/package=PPMiss .
First Published: 2023-03-19
Latest Update: 2023-09-04
Description:
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.
How to cite:
Taiane Schaedler Prass (2023). PPMiss: Copula-Based Estimator for Long-Range Dependent Processes under Missing Data. R package version 0.1.1, https://cran.r-project.org/web/packages/PPMiss. Accessed 03 Apr. 2025.
Previous versions and publish date:
0.1.0 (2023-03-19 23:20)
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