Package: L0ggm
Title: Smooth L0 Penalty Approximations for Gaussian Graphical Models
Version: 0.0.1
Date: 2026-03-21
Authors@R: c(
    person("Alexander", "Christensen", email = "alexpaulchristensen@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-9798-7037")),
    person("Jeongwon", "Choi", email = "jungwon799@gmail.com", role = "ctb", comment = c(ORCID = "0000-0001-6087-2124")),
    person("John", "Fox", role = c("cph", "ctb"), comment = "Original implementation of polyserial correlations in auto_correlate.R"),
    person("Yves", "Rosseel", role = c("cph", "ctb"), comment = "Original implementation of rmsea_ci in network_fit.R"),
    person("Alexander", "Robitzsch", role = c("cph", "ctb"), comment = "C++ implementation of Drezner-Wesolowsky bivariate normal CDF in polychoric_matrix.c"),
    person("David", "Blackman", role = "ctb", comment = "Original xoshiro.c implementation"),
    person("Sebastiano", "Vigna", role = "ctb", comment = "Original xoshiro.c implementation"),
    person("John", "Burkardt", role = c("cph", "ctb"), comment = "Original ziggurat.c implementation")
   )
Description: Provides smooth approximations to the L0 norm penalty for
    estimating sparse Gaussian graphical models (GGMs). Network estimation
    is performed using the Local Linear Approximation (LLA) framework
    (Fan & Li, 2001 <doi:10.1198/016214501753382273>;
    Zou & Li, 2008 <doi:10.1214/009053607000000802>) with five penalty
    functions: arctangent (Wang & Zhu, 2016 <doi:10.1155/2016/6495417>),
    EXP (Wang, Fan, & Zhu, 2018 <doi:10.1007/s10463-016-0588-3>), Gumbel,
    Log (Candes, Wakin, & Boyd, 2008 <doi:10.1007/s00041-008-9045-x>),
    and Weibull. Adaptive penalty parameters for EXP, Gumbel, and Weibull
    are estimated via maximum likelihood, and model selection uses
    information criteria including AIC, BIC, and EBIC (Extended BIC).
    Simulation functions generate multivariate normal data from GGMs with
    stochastic block model or small-world (Watts-Strogatz) network structures.
Depends: R (>= 3.5.0)
License: AGPL (>= 3.0)
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Imports: igraph, glasso, glassoFast, Matrix, methods, psych, stats
Copyright: See inst/COPYRIGHTS for details
BugReports: https://github.com/AlexChristensen/L0ggm/issues
RoxygenNote: 7.3.3
Packaged: 2026-03-21 16:01:20 UTC; alextops
Author: Alexander Christensen [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-9798-7037>),
  Jeongwon Choi [ctb] (ORCID: <https://orcid.org/0000-0001-6087-2124>),
  John Fox [cph, ctb] (Original implementation of polyserial correlations
    in auto_correlate.R),
  Yves Rosseel [cph, ctb] (Original implementation of rmsea_ci in
    network_fit.R),
  Alexander Robitzsch [cph, ctb] (C++ implementation of
    Drezner-Wesolowsky bivariate normal CDF in polychoric_matrix.c),
  David Blackman [ctb] (Original xoshiro.c implementation),
  Sebastiano Vigna [ctb] (Original xoshiro.c implementation),
  John Burkardt [cph, ctb] (Original ziggurat.c implementation)
Maintainer: Alexander Christensen <alexpaulchristensen@gmail.com>
Repository: CRAN
Date/Publication: 2026-03-26 09:30:27 UTC
Built: R 4.6.0; aarch64-apple-darwin23; 2026-04-26 04:02:37 UTC; unix
Archs: L0ggm.so.dSYM
