Package: outliers.ts.oga
Type: Package
Title: Efficient Outlier Detection for Large Time Series Databases
Version: 1.1.2
Authors@R: 
  c(person(given = "Pedro",
           family = "Galeano",
           email = "pedro.galeano@uc3m.es",
           role = c("aut","cre"),
           comment = c(ORCID="0000-0003-2577-2747")),
    person(given = "Daniel",
           family = "Peña",
           email = "daniel.pena@uc3m.es",
           role = "aut",
           comment = c(ORCID="0000-0002-9137-1557")),
    person(given = "Ruey S.",
           family = "Tsay",
           email = "ruey.tsay@chicagobooth.edu",
           role = "aut",
           comment = c(ORCID="0000-0002-4949-4035"))
           )
Maintainer: Pedro Galeano <pedro.galeano@uc3m.es>
Description: Programs for detecting and cleaning outliers in single time series and in time series from homogeneous and heterogeneous databases using an Orthogonal Greedy Algorithm (OGA) for saturated linear regression models. The programs implement the procedures presented in the paper entitled "Efficient Outlier Detection for Large Time Series Databases" by Pedro Galeano, Daniel Peña and Ruey S. Tsay (2026), working paper, Universidad Carlos III de Madrid. Version 1.1.2 fixes one bug.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.3.0)
Imports: caret (>= 6.0-94), forecast (>= 8.22.0), future (>= 1.67.0),
        future.apply (>= 1.20.0), gsarima (>= 0.1-5), parallelly (>=
        1.37.1), robust (>= 0.7-4)
Suggests: knitr, rmarkdown
NeedsCompilation: no
Author: Pedro Galeano [aut, cre] (ORCID:
    <https://orcid.org/0000-0003-2577-2747>),
  Daniel Peña [aut] (ORCID: <https://orcid.org/0000-0002-9137-1557>),
  Ruey S. Tsay [aut] (ORCID: <https://orcid.org/0000-0002-4949-4035>)
LazyData: true
RoxygenNote: 7.3.3
Packaged: 2026-01-30 11:54:34 UTC; PGALEANO
Repository: CRAN
Date/Publication: 2026-01-30 14:30:02 UTC
Built: R 4.6.0; ; 2026-04-25 13:48:25 UTC; unix
