Package: starma 1.3

starma: Modelling Space Time AutoRegressive Moving Average (STARMA) Processes

Statistical functions to identify, estimate and diagnose a Space-Time AutoRegressive Moving Average (STARMA) model.

Authors:Felix Cheysson

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starma.pdf |starma.html✨
starma/json (API)

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

Peer review:

Bug tracker:https://github.com/fcheysson/starma/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • blist - Neighbourhood weight matrices for France's 94 departments
  • dlist - Neighbourhood weight matrices for France's 94 departments
  • klist - Neighbourhood weight matrices for France's 94 departments

On CRAN:

2.38 score 2 stars 12 scripts 283 downloads 17 exports 30 dependencies

Last updated 3 years agofrom:2e08ba5e12. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 19 2024
R-4.5-win-x86_64NOTENov 19 2024
R-4.5-linux-x86_64NOTENov 19 2024
R-4.4-win-x86_64NOTENov 19 2024
R-4.4-mac-x86_64NOTENov 19 2024
R-4.4-mac-aarch64NOTENov 19 2024
R-4.3-win-x86_64NOTENov 19 2024
R-4.3-mac-x86_64NOTENov 19 2024
R-4.3-mac-aarch64NOTENov 19 2024

Exports:print.starmaprint.stcor.testprint.summary.starmastacfstacfCPPstarmastarma.defaultstarmaCPPstcenterstcor.teststcor.test.defaultstcovstcovCPPstpacfstpacfCPPstplotsummary.starma

Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppArmadillorlangscalestibbleutf8vctrsviridisLitewithr