funbootband: Simultaneous Prediction and Confidence Bands for Time Series Data

Provides methods to compute simultaneous prediction and confidence bands for dense time series data. The implementation builds on the functional bootstrap approach proposed by Lenhoff et al. (1999) <doi:10.1016/S0966-6362(98)00043-5> and extended by Koska et al. (2023) <doi:10.1016/j.jbiomech.2023.111506> to support both independent and clustered (hierarchical) data. Includes a simple API (see band()) and an 'Rcpp' backend for performance.

Version: 0.2.0
Depends: R (≥ 3.5)
Imports: Rcpp, stats
LinkingTo: Rcpp
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown
Published: 2025-10-20
DOI: 10.32614/CRAN.package.funbootband
Author: Daniel Koska ORCID iD [aut, cre, cph]
Maintainer: Daniel Koska <dkoska at proton.me>
BugReports: https://github.com/koda86/funbootband-cran/issues
License: GPL-3
URL: https://github.com/koda86/funbootband-cran
NeedsCompilation: yes
SystemRequirements: C++17
Materials: README, NEWS
CRAN checks: funbootband results

Documentation:

Reference manual: funbootband.html , funbootband.pdf
Vignettes: funbootband: Simultaneous Prediction and Confidence Bands for Time Series Data (source, R code)

Downloads:

Package source: funbootband_0.2.0.tar.gz
Windows binaries: r-devel: funbootband_0.2.0.zip, r-release: funbootband_0.2.0.zip, r-oldrel: funbootband_0.2.0.zip
macOS binaries: r-release (arm64): funbootband_0.2.0.tgz, r-oldrel (arm64): funbootband_0.2.0.tgz, r-release (x86_64): funbootband_0.2.0.tgz, r-oldrel (x86_64): funbootband_0.2.0.tgz

Linking:

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