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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.
Version: | 0.10.2 |
Depends: | R (≥ 3.5.0) |
Imports: | Rcpp |
LinkingTo: | Rcpp, RcppArmadillo |
Suggests: | testthat (≥ 3.0.0) |
Published: | 2024-06-20 |
DOI: | 10.32614/CRAN.package.BTtest |
Author: | Paul Haimerl |
Maintainer: | Paul Haimerl <p.haimerl at student.maastrichtuniversity.nl> |
BugReports: | https://github.com/Paul-Haimerl/BTtest/issues |
License: | GPL (≥ 3) |
URL: | https://github.com/Paul-Haimerl/BTtest |
NeedsCompilation: | yes |
Materials: | README NEWS |
CRAN checks: | BTtest results |
Reference manual: | BTtest.pdf |
Package source: | BTtest_0.10.2.tar.gz |
Windows binaries: | r-devel: BTtest_0.10.2.zip, r-release: BTtest_0.10.2.zip, r-oldrel: BTtest_0.10.2.zip |
macOS binaries: | r-release (arm64): BTtest_0.10.2.tgz, r-oldrel (arm64): BTtest_0.10.2.tgz, r-release (x86_64): BTtest_0.10.2.tgz, r-oldrel (x86_64): BTtest_0.10.2.tgz |
Old sources: | BTtest archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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