Package: hts 6.0.3

Earo Wang

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://robjhyndman.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

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

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:

forecastshts

9.35 score 110 stars 5 packages 200 scripts 4.5k downloads 6 mentions 18 exports 47 dependencies

Last updated 4 months agofrom:1408ab2c5c. Checks:OK: 9. Indexed: no.

TargetResultDate
Doc / VignettesOKOct 28 2024
R-4.5-win-x86_64OKOct 28 2024
R-4.5-linux-x86_64OKOct 28 2024
R-4.4-win-x86_64OKOct 28 2024
R-4.4-mac-x86_64OKOct 28 2024
R-4.4-mac-aarch64OKOct 28 2024
R-4.3-win-x86_64OKOct 28 2024
R-4.3-mac-x86_64OKOct 28 2024
R-4.3-mac-aarch64OKOct 28 2024

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

Dependencies:clicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadilloRcppEigenrlangscalesSparseMtibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo