Package: PAGFL
Title: Joint Estimation and Identification of Latent Groups in Panel
        Data Models
Version: 1.0.1
Authors@R: c(
    person("Paul", "Haimerl", email = "paul.haimerl@maastrichtuniversity.nl", role = c("aut","cre"), comment = c(ORCID = "0000-0003-3198-8317")),
    person("Ali", "Mehrabani", email = "ali.mehrabani@email.ucr.edu", role = "ctb", comment = c(ORCID = "0000-0002-1848-5582")))
Maintainer: Paul Haimerl <paul.haimerl@maastrichtuniversity.nl>
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) <doi:10.1016/j.jeconom.2022.12.002>. 
    PAGFL is an efficient methodology to identify latent group structures and estimate group-specific coefficients simultaneously. 
License: AGPL (>= 3)
Encoding: UTF-8
RoxygenNote: 7.2.3
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp, pbapply
BugReports: https://github.com/Paul-Haimerl/PAGFL/issues
URL: https://github.com/Paul-Haimerl/PAGFL
NeedsCompilation: yes
Packaged: 2024-02-16 21:52:58 UTC; PaulAdmin
Author: Paul Haimerl [aut, cre] (<https://orcid.org/0000-0003-3198-8317>),
  Ali Mehrabani [ctb] (<https://orcid.org/0000-0002-1848-5582>)
Repository: CRAN
Date/Publication: 2024-02-17 11:10:05 UTC
