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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "fgls" in publications use:'
type: software
license: MIT
title: 'fgls: Feasible GLS for Serial Correlation and Heteroskedasticity'
version: 0.1.0
doi: 10.1016/j.jeconom.2026.106346
abstract: Feasible generalized least squares (FGLS) estimators for linear regressions
  whose errors are serially correlated, heteroskedastic of unknown form, or both.
  Serial correlation is handled by the autoregressive filter of Perron and González-Coya
  (2026) <https://doi.org/10.1016/j.jeconom.2026.106346>, estimated from a Durbin
  regression whose order is chosen by an information criterion, with a variance estimator
  that stays valid when the regressors are only pre-determined rather than strictly
  exogenous. Heteroskedasticity is handled by the adaptive Lasso estimate of the skedastic
  function of González-Coya and Perron (2024) <https://doi.org/10.1515/jem-2023-0007>,
  with a bias-corrected sandwich variance. Both corrections can be combined. Benchmark
  estimators (ordinary least squares with heteroskedasticity and autocorrelation consistent
  standard errors, Cochrane-Orcutt, infeasible GLS) and the simulation designs of
  both papers are included.
authors:
- family-names: González-Coya
  given-names: Emilio
  email: emiliogc@bu.edu
  orcid: https://orcid.org/0009-0001-0362-8843
preferred-citation:
  type: article
  title: Feasible GLS for Time Series Regression
  authors:
  - family-names: Perron
    given-names: Pierre
  - family-names: González-Coya
    given-names: Emilio
    email: emiliogc@bu.edu
    orcid: https://orcid.org/0009-0001-0362-8843
  journal: Journal of Econometrics
  year: '2026'
  volume: '258'
  doi: 10.1016/j.jeconom.2026.106346
  start: '106346'
repository: https://cran.r-universe.dev
repository-code: https://github.com/emiliogcs/fgls
commit: a32f0812edf20c211b54cf525967a9f1b6f41dda
url: https://emiliogcs.com/fgls/
date-released: '2026-11-07'
contact:
- family-names: González-Coya
  given-names: Emilio
  email: emiliogc@bu.edu
  orcid: https://orcid.org/0009-0001-0362-8843
references:
- type: article
  title: 'Estimation in the Presence of Heteroskedasticity of Unknown Form: A Lasso-based
    Approach'
  authors:
  - family-names: González-Coya
    given-names: Emilio
  - family-names: Perron
    given-names: Pierre
  journal: Journal of Econometric Methods
  year: '2024'
  volume: '13'
  issue: '1'
  doi: 10.1515/jem-2023-0007
  start: '29'
  end: '48'
- type: manual
  title: 'fgls: Feasible GLS for Serial Correlation and Heteroskedasticity'
  authors:
  - family-names: González-Coya
    given-names: Emilio
  year: '2026'
  notes: R package version 0.1.0
  url: https://github.com/emiliogcs/fgls