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PPMiss  

Copula-Based Estimator for Long-Range Dependent Processes under Missing Data
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]
All associated links for this package
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 07 Nov. 2024.
Previous versions and publish date:
0.1.0 (2023-03-19 23:20)
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Complete documentation for PPMiss
Functions, R codes and Examples using the PPMiss R package
Full PPMiss package functions and examples
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