Package: strucchangeRcpp
Version: 1.5-4-1.0.0
Title: Testing, Monitoring, and Dating Structural Changes: C++ Version
Authors@R: c(person(given = "Dainius", family = "Masiliunas", role = c("aut", "cre"),
             email = "pastas4@gmail.com", comment = c(ORCID = "0000-0001-5654-1277")),
             person(given = "Achim", family = "Zeileis", role = c("aut"), email = "Achim.Zeileis@R-project.org",
                    comment = c(ORCID = "0000-0003-0918-3766")),
             person(given = "Marius", family = "Appel", role = "aut", email = "marius.appel@uni-muenster.de"),
             person(given = "Friedrich", family = "Leisch", role = "aut", email = "Friedrich.Leisch@R-project.org"),
             person(given = "Kurt", family = "Hornik", role = "aut", email = "Kurt.Hornik@R-project.org"),
             person(given = "Christian", family = "Kleiber", role = "aut", email = "Christian.Kleiber@unibas.ch"),
             person(given = "Andrei", family = "Mirt", role = "ctb", email = "andrei.mirt@wur.nl",
                    comment = c(ORCID = "0000-0003-3654-2090")),
             person(given = "Bruce", family = "Hansen", role = "ctb"),
             person(given = c("Edgar", "C."), family = "Merkle", role = "ctb"),
             person(given = "Nikolaus", family = "Umlauf", role = "ctb"))
Description: A fast implementation with additional experimental features for
             testing, monitoring and dating structural changes in (linear)
             regression models. 'strucchangeRcpp' features tests/methods from
	     the generalized fluctuation test framework as well as from
	     the F test (Chow test) framework. This includes methods to
             fit, plot and test fluctuation processes (e.g. cumulative/moving
             sum, recursive/moving estimates) and F statistics, respectively.
             These methods are described in Zeileis et al. (2002)
             <doi:10.18637/jss.v007.i02>.
             Finally, the breakpoints in regression models with structural
             changes can be estimated together with confidence intervals,
             and their magnitude as well as the model fit can be evaluated
             using a variety of statistical measures.
LazyData: yes
LinkingTo: Rcpp, RcppArmadillo
Depends:
    R (>= 2.10.0),
    zoo,
    sandwich
Suggests:
    stats4,
    car,
    dynlm,
    e1071,
    foreach,
    lmtest,
    mvtnorm,
    tseries,
    bfast
Imports:
    graphics,
    stats,
    Rcpp (>= 0.12.7),
    utils
License: GPL-2 | GPL-3
URL: https://github.com/bfast2/strucchangeRcpp/
BugReports: https://github.com/bfast2/strucchangeRcpp/issues
RoxygenNote: 7.1.1
Encoding: UTF-8
