Package: hts 6.0.3

hts: Hierarchical and Grouped Time Series

Provides methods for analysing and forecasting hierarchical and grouped time series. The available forecast methods include bottom-up, top-down, optimal combination reconciliation (Hyndman et al. 2011) <doi:10.1016/j.csda.2011.03.006>, and trace minimization reconciliation (Wickramasuriya et al. 2018) <doi:10.1080/01621459.2018.1448825>.

Authors:Rob Hyndman [aut], Alan Lee [aut], Earo Wang [aut, cre], Shanika Wickramasuriya [aut]

hts_6.0.3.tar.gz
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hts.pdf |hts.html
hts/json (API)
NEWS

# Install 'hts' in R:
install.packages('hts', repos = c('https://earowang.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/earowang/hts/issues

Pkgdown site:https://pkg.earo.me

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • htseg1 - Simple examples of hierarchical time series.
  • htseg2 - Simple examples of hierarchical time series.
  • infantgts - Regional infant mortality counts across Australia from 1933 to 2003.

On CRAN:

forecastshtscpp

9.67 score 110 stars 5 packages 214 scripts 4.4k downloads 6 mentions 18 exports 47 dependencies

Last updated 27 days agofrom:7e08414899. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKDec 25 2024
R-4.5-win-x86_64OKDec 25 2024
R-4.5-linux-x86_64OKDec 25 2024
R-4.4-win-x86_64OKDec 25 2024
R-4.4-mac-x86_64OKDec 25 2024
R-4.4-mac-aarch64OKDec 25 2024
R-4.3-win-x86_64OKDec 25 2024
R-4.3-mac-x86_64OKDec 25 2024
R-4.3-mac-aarch64OKDec 25 2024

Exports:accuracy.gtsaggtsalltscombinefforecast.gtsget_groupsget_nodesgtshtsis.gtsis.htsMinTplot.gtsprint.gtsprint.htssmatrixsummary.gtssummary.hts

Dependencies:clicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadilloRcppEigenrlangscalesSparseMtibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo