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PPMiss (version 0.1.1)

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

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.

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Version

Install

install.packages('PPMiss')

Monthly Downloads

131

Version

0.1.1

License

GPL (>= 3)

Maintainer

Taiane Schaedler Prass

Last Published

September 4th, 2023

Functions in PPMiss (0.1.1)

k1fun

Constant K1
PPMiss.Package

PPMiss: Copula-Based Estimator for Long-Range Dependent Processes under Missing Data.
kdens

Kernel density estimator
arfima.coefs

Coefficients of an ARFIMA(p,d,q) model
d.fit

Long memory parameter estimation
PPMiss.copulas

Copula functions and the corresponding derivative limit.