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-4.7-arm64)starma_1.3.tar.gz(r-4.7-x86_64)starma_1.3.tar.gz(r-4.6-arm64)starma_1.3.tar.gz(r-4.6-x86_64)
starma_1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
starma/json (API)

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

Conda:

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

openblascpp

1.62 score 3 stars 14 scripts 261 downloads 17 exports 19 dependencies

Last updated from:1e5d9bf53f. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK140
linux-devel-x86_64OK129
source / vignettesOK191
linux-release-arm64OK143
linux-release-x86_64OK206
wasm-releaseOK129

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

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecycleR6RColorBrewerRcppRcppArmadillorlangS7scalesvctrsviridisLitewithr