PAGFL: Joint Estimation of Latent Groups and Group-Specific Coefficients in Panel Data Models

Latent group structures are a common challenge in panel data analysis. Disregarding group-level heterogeneity can introduce bias. Conversely, estimating individual coefficients for each cross-sectional unit is inefficient and may lead to high uncertainty. This package addresses the issue of unobservable group structures by implementing the pairwise adaptive group fused Lasso (PAGFL) by Mehrabani (2023) <doi:10.1016/j.jeconom.2022.12.002>. PAGFL identifies latent group structures and group-specific coefficients in a single step. On top of that, we extend the PAGFL to time-varying coefficient functions.

Version: 1.1.0
Depends: R (≥ 3.5.0)
Imports: Rcpp, lifecycle, ggplot2, RcppParallel
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
Suggests: testthat (≥ 3.0.0)
Published: 2024-06-08
DOI: 10.32614/CRAN.package.PAGFL
Author: Paul Haimerl ORCID iD [aut, cre], Stephan Smeekes ORCID iD [ctb], Ines Wilms ORCID iD [ctb], Ali Mehrabani ORCID iD [ctb]
Maintainer: Paul Haimerl <p.haimerl at>
License: AGPL (≥ 3)
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: PAGFL results


Reference manual: PAGFL.pdf


Package source: PAGFL_1.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): PAGFL_1.1.0.tgz, r-oldrel (arm64): PAGFL_1.1.0.tgz, r-release (x86_64): PAGFL_1.1.0.tgz, r-oldrel (x86_64): PAGFL_1.1.0.tgz
Old sources: PAGFL archive


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