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PAGFL  

Joint Estimation of Latent Groups and Group-Specific Coefficients in (Time-Varying) Panel Data Models
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", "1.1.4")



Attach the package and use:
library("PAGFL")
Maintained by
Paul Haimerl
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-02-16
Latest Update: 2025-02-20
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 (Time-Varying) Panel Data Models. R package version 1.1.4, https://cran.r-project.org/web/packages/PAGFL. Accessed 12 Sep. 2026.
Previous versions and publish date:
(2026-07-09 08:15), 1.0.0 (2024-02-16 16:00), 1.0.1 (2024-02-17 12:10), 1.1.0 (2024-06-08 23:20), 1.1.1 (2024-07-23 19:00), 1.1.2 (2024-11-09 23:10), 1.1.3 (2025-02-20 14:10)
Other packages that cited PAGFL R package
View PAGFL citation profile
Other R packages that PAGFL depends, imports, suggests or enhances
Complete documentation for PAGFL
Functions, R codes and Examples using the PAGFL R package
Full PAGFL package functions and examples
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