Package: PAGFL 1.2.0

PAGFL: Joint Estimation of Latent Groups and Group-Specific Coefficients in (Time-Varying) 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 (FUSE-TIME), following Haimerl et al. (2025) <doi:10.48550/arXiv.2503.23165>.

Authors:Paul Haimerl [aut, cre], Stephan Smeekes [ctb], Ines Wilms [ctb], Ali Mehrabani [ctb]

PAGFL_1.2.0.tar.gz
PAGFL_1.2.0.zip(r-4.7)PAGFL_1.2.0.zip(r-4.6)PAGFL_1.2.0.zip(r-4.5)
PAGFL_1.2.0.tgz(r-4.6-x86_64)PAGFL_1.2.0.tgz(r-4.6-arm64)PAGFL_1.2.0.tgz(r-4.5-x86_64)PAGFL_1.2.0.tgz(r-4.5-arm64)
PAGFL_1.2.0.tar.gz(r-4.7-arm64)PAGFL_1.2.0.tar.gz(r-4.7-x86_64)PAGFL_1.2.0.tar.gz(r-4.6-arm64)PAGFL_1.2.0.tar.gz(r-4.6-x86_64)
PAGFL_1.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
PAGFL/json (API)
NEWS

# Install 'PAGFL' in R:
install.packages('PAGFL', repos = c('https://paul-haimerl.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/paul-haimerl/pagfl/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

classificationpanel-data-modeltime-varying-coefficientsopenblascppopenmp

4.39 score 7 stars 7 scripts 173 downloads 8 exports 22 dependencies

Last updated from:b2fd55eb0e. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK141
linux-devel-x86_64OK140
source / vignettesOK207
linux-release-arm64OK138
linux-release-x86_64OK198
macos-release-arm64OK109
macos-release-x86_64OK180
macos-oldrel-arm64OK119
macos-oldrel-x86_64OK388
windows-develOK174
windows-releaseOK169
windows-oldrelOK210
wasm-releaseOK114

Exports:fuse_timegrouped_plmgrouped_tv_plmpagflPAGFLsim_DGPsim_tv_DGPtv_pagfl

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecycleR6RColorBrewerRcppRcppArmadilloRcppParallelRcppThreadRhpcBLASctlrlangS7scalesvctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Fused Unobserved group Spline Estimation of TIME varying coefficientscoef.fusetime df.residual.fusetime fitted.fusetime formula.fusetime fuse_time print.fusetime residuals.fusetime summary.fusetime tv_pagfl
Grouped Panel Data Modelcoef.gplm df.residual.gplm fitted.gplm formula.gplm grouped_plm print.gplm residuals.gplm summary.gplm
Grouped Time-varying Panel Data Modelcoef.tv_gplm df.residual.tv_gplm fitted.tv_gplm formula.tv_gplm grouped_tv_plm print.tv_gplm residuals.tv_gplm summary.tv_gplm
Pairwise Adaptive Group Fused Lassocoef.pagfl df.residual.pagfl fitted.pagfl formula.pagfl PAGFL pagfl print.pagfl residuals.pagfl summary.pagfl
Simulate a Panel With a Group Structure in the Slope Coefficientssim_DGP
Simulate a Time-varying Panel With a Group Structure in the Slope Coefficientssim_tv_DGP