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PAGFL
View on CRAN: Click
here
Download and install PAGFL package within the R console
Install from CRAN:
install.packages("PAGFL")
Install from Github:
library("remotes")
install_github("cran/PAGFL")
Install by package version:
library("remotes")
install_version("PAGFL", "1.1.3")
Attach the package and use:
library("PAGFL")
Maintained by
Paul Haimerl
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.PAGFL . https://github.com/Paul-Haimerl/PAGFL/issues . https://github.com/Paul-Haimerl/PAGFL . PAGFL results . PAGFL.pdf . PAGFL_1.1.3.tar.gz . PAGFL_1.1.3.zip . PAGFL_1.1.3.zip . PAGFL_1.1.3.zip . PAGFL_1.1.3.tgz . PAGFL_1.1.3.tgz . PAGFL_1.1.3.tgz . PAGFL_1.1.3.tgz . PAGFL archive . https://CRAN.R-project.org/package=PAGFL .
First Published: 2024-02-16
Latest Update: 2024-02-17
Description:
In panel data analysis, unobservable group structures are a common challenge. Disregarding group-level heterogeneity by assuming an entirely homogeneous panel can introduce bias. Conversely, estimating individual coefficients for each cross-sectional unit is inefficient and may lead to high uncertainty.
This package addresses this issue by implementing the pairwise adaptive group fused Lasso (PAGFL) by Mehrabani (2023) .
PAGFL is an efficient methodology to identify latent group structures and estimate group-specific coefficients simultaneously.
How to cite:
Paul Haimerl (2024). PAGFL: Joint Estimation of Latent Groups and Group-Specific Coefficients in Panel Data Models. R package version 1.1.3, https://cran.r-project.org/web/packages/PAGFL. Accessed 12 May. 2025.
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