Package: starma 1.3

Felix Cheysson

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

starma_1.3.tar.gz
starma_1.3.tar.gz(r-4.5-noble)starma_1.3.tar.gz(r-4.4-noble)
starma_1.3.tgz(r-4.4-emscripten)starma_1.3.tgz(r-4.3-emscripten)
starma.pdf |starma.html✨
starma/json (API)

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

Peer review:

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

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascpp

1.56 score 3 stars 12 scripts 271 downloads 17 exports 30 dependencies

Last updated 9 years agofrom:1e5d9bf53f. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 02 2024
R-4.5-linux-x86_64OKDec 02 2024

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

Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppArmadillorlangscalestibbleutf8vctrsviridisLitewithr