Package: BTtest
Title: Estimate the Number of Factors in Large Nonstationary Datasets
Version: 0.10.3
Authors@R: 
    person("Paul", "Haimerl", , "paul.haimerl@econ.au.dk", role = c("aut", "cre"),
           comment = c(ORCID = "0000-0003-3198-8317"))
Maintainer: Paul Haimerl <paul.haimerl@econ.au.dk>
Description: Large panel data sets are often subject to common trends.
        However, it can be difficult to determine the exact number of
        these common factors and analyse their properties. The package
        implements the Barigozzi and Trapani (2022)
        <doi:10.1080/07350015.2021.1901719> test, which not only
        provides an efficient way of estimating the number of common
        factors in large nonstationary panel data sets, but also gives
        further insights on factor classes. The routine identifies the
        existence of (i) a factor subject to a linear trend, (ii) the
        number of zero-mean I(1) and (iii) zero-mean I(0) factors.
        Furthermore, the package includes the Integrated Panel Criteria
        by Bai (2004) <doi:10.1016/j.jeconom.2003.10.022> that provide
        a complementary measure for the number of factors.
License: GPL (>= 3)
Encoding: UTF-8
BugReports: https://github.com/Paul-Haimerl/BTtest/issues
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.1
URL: https://github.com/Paul-Haimerl/BTtest
Imports: Rcpp
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
Repository: https://paul-haimerl.r-universe.dev
Date/Publication: 2025-03-03 21:21:40 UTC
RemoteUrl: https://github.com/paul-haimerl/bttest
RemoteRef: HEAD
RemoteSha: efab0bc37d870d0e212a0df827aeb1dc1c2d6b78
NeedsCompilation: yes
Packaged: 2026-10-05 09:24:34 UTC; root
Author: Paul Haimerl [aut, cre] (ORCID:
    <https://orcid.org/0000-0003-3198-8317>)
Depends: R (>= 3.5.0)