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funtimes: Functions for Time Series Analysis

Nonparametric estimators and tests for time series analysis. The functions use bootstrap techniques and robust nonparametric difference-based estimators to test for the presence of possibly non-monotonic trends and for synchronicity of trends in multiple time series.

Version: 9.1
Depends: R (≥ 3.5.0)
Imports: dbscan, Kendall, lmtest, mlVAR, parallel, Rdpack, sandwich, vars
Suggests: covid19us, Ecdat, ggplot2, gridExtra, knitr, patchwork, randomcoloR, readxl, reshape2, rmarkdown
Published: 2023-03-21
Author: Vyacheslav Lyubchich ORCID iD [aut, cre], Yulia R. Gel [aut], Alexander Brenning [ctb], Calvin Chu [ctb], Xin Huang [ctb], Umar Islambekov [ctb], Palina Niamkova [ctb], Dorcas Ofori-Boateng [ctb], Ethan D. Schaeffer [ctb], Srishti Vishwakarma [aut], Xingyu Wang [ctb]
Maintainer: Vyacheslav Lyubchich <lyubchich at umces.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
In views: TimeSeries
CRAN checks: funtimes results

Documentation:

Reference manual: funtimes.pdf
Vignettes: Beale's estimator and sample size calculation
Tests for trends in time series
Clustering time series using funtimes package

Downloads:

Package source: funtimes_9.1.tar.gz
Windows binaries: r-devel: funtimes_9.1.zip, r-release: funtimes_9.1.zip, r-oldrel: funtimes_9.1.zip
macOS binaries: r-release (arm64): funtimes_9.1.tgz, r-oldrel (arm64): funtimes_9.1.tgz, r-release (x86_64): funtimes_9.1.tgz, r-oldrel (x86_64): funtimes_9.1.tgz
Old sources: funtimes 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.
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