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qfa: Quantile-Frequency Analysis (QFA) of Time Series

Quantile-frequency analysis (QFA) of univariate or multivariate time series based on trigonometric quantile regression. See Li, T.-H. (2012) "Quantile periodograms", Journal of the American Statistical Association, 107, 765–776, <doi:10.1080/01621459.2012.682815>; Li, T.-H. (2014) Time Series with Mixed Spectra, CRC Press, <doi:10.1201/b15154>; Li, T.-H. (2022) "Quantile Fourier transform, quantile series, and nonparametric estimation of quantile spectra", <doi:10.48550/arXiv.2211.05844>.

Version: 2.1
Depends: R (≥ 3.5)
Imports: RhpcBLASctl, doParallel, fields, foreach, mgcv, nlme, parallel, quantreg, splines, stats, graphics, colorRamps, MASS
Published: 2023-08-21
DOI: 10.32614/CRAN.package.qfa
Author: Ta-Hsin Li [cre, aut]
Maintainer: Ta-Hsin Li <thl at us.ibm.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://www.r-project.org, https://github.com/IBM/qfa
NeedsCompilation: yes
CRAN checks: qfa results

Documentation:

Reference manual: qfa.pdf

Downloads:

Package source: qfa_2.1.tar.gz
Windows binaries: r-devel: qfa_2.1.zip, r-release: qfa_2.1.zip, r-oldrel: qfa_2.1.zip
macOS binaries: r-release (arm64): qfa_2.1.tgz, r-oldrel (arm64): qfa_2.1.tgz, r-release (x86_64): qfa_2.1.tgz, r-oldrel (x86_64): qfa_2.1.tgz
Old sources: qfa archive

Linking:

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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.