Package: CoSMoS 2.2.0

Kevin Shook

CoSMoS: Complete Stochastic Modelling Solution

Makes univariate, multivariate, or random fields simulations precise and simple. Just select the desired time series or random fields’ properties and it will do the rest. CoSMoS is based on the framework described in Papalexiou (2018, <doi:10.1016/j.advwatres.2018.02.013>), extended for random fields in Papalexiou and Serinaldi (2020, <doi:10.1029/2019WR026331>), and further advanced in Papalexiou et al. (2021, <doi:10.1029/2020WR029466>) to allow fine-scale space-time simulation of storms (or even cyclone-mimicking fields).

Authors:Simon Michael Papalexiou [aut], Francesco Serinaldi [aut], Filip Strnad [aut], Yannis Markonis [aut], Kevin Shook [ctb, cre]

CoSMoS_2.2.0.tar.gz
CoSMoS_2.2.0.tar.gz(r-4.7-arm64)CoSMoS_2.2.0.tar.gz(r-4.7-x86_64)CoSMoS_2.2.0.tar.gz(r-4.6-arm64)CoSMoS_2.2.0.tar.gz(r-4.6-x86_64)
CoSMoS_2.2.0.tgz(r-4.6-emscripten)CoSMoS_2.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
CoSMoS/json (API)
NEWS

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

Bug tracker:https://github.com/tychelab/cosmos/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • disch - Daily streamflow data data
  • precip - Hourly station precipitation data

On CRAN:

Conda:

cppopenmp

5.53 score 3 stars 75 scripts 394 downloads 28 mentions 66 exports 39 dependencies

Last updated from:138e9874bd. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK230
linux-devel-x86_64OK239
source / vignettesOK296
linux-release-arm64OK229
linux-release-x86_64OK203
wasm-releaseOK192

Exports:acsactfactfdiscreteactfInvactiactpntsactpntsB6advectionFadvectionFhyperbolicadvectionFradialadvectionFrotationadvectionFspiraladvectionFspiralCEadvectionFuniformanalyzeTSanisotropyTanisotropyTaffineanisotropyTswirlanisotropyTwavecheckRFcheckTSdburrIIIdburrXIIdgevdggammadparetoIIfitACSfitactffitDistfitVARgenerateMTSgenerateMTSFastgenerateRFgenerateRFFastgenerateTSmburrIIImburrXIImgevmggammamomentsmparetoIIpburrIIIpburrXIIpgevpggammapopulationstatpparetoIIqburrIIIqburrXIIqgevqggammaqparetoIIquickTSPlotrburrIIIrburrXIIregenerateTSreportTSrgevrggammarparetoIIsample.momentssimulateTSstcfclaytonstcfgneiting14stcfgneiting16stcs

Dependencies:animationBHclicpp11curldata.tablefarverggplot2ggquivergluegtableisobandlabelinglatticelifecyclemagickmagrittrmArMASSMatrixmatrixcalcMBAmisc3dmvtnormnloptrpatchworkplot3DpracmaR6RColorBrewerRcppRcppEigenRcppNumericalrlangS7scalesvctrsviridisLitewithr

CoSMoS R | Complete Stochastic Modelling Solution

Simon Michael Papalexiou, Francesco Serinaldi, Filip Strnad, Yannis Markonis, Kevin Shook

Rendered fromvignette.Rmdusingknitr::rmarkdownon May 28 2026.

Last update: 2026-05-07
Started: 2019-04-11

Readme and manuals

Help Manual

Help pageTopics
CoSMoS: Complete Stochastic Modelling SolutionCoSMoS-package CoSMoS
AutoCorrelation Structureacs
AutoCorrelation Transformed Pointsactpnts
AutoCorrelation Transformed Points for Bardossy dependence structureactpntsB6
Advection fieldsadvectionF
Hyperbolic advection fieldadvectionFhyperbolic
Radial advection fieldadvectionFradial
Rotational advection fieldadvectionFrotation
Spiraling advection fieldadvectionFspiral
Spiraling advection field satisfying continuity equationadvectionFspiralCE
Uniform advection fieldadvectionFuniform
Analyse, report, and simulate seasonal time seriesanalyzeTS reportTS simulateTS
Anisotropy transformationanisotropyT
Affine anisotropy transformationanisotropyTaffine
Swirl anisotropy transformationanisotropyTswirl
Wave anisotropy transformationanisotropyTwave
Burr Type III distributionBurrIII dburrIII mburrIII pburrIII qburrIII rburrIII
Burr Type XII distributionBurrXII dburrXII mburrXII pburrXII qburrXII rburrXII
Numerical and visual check of generated random fieldscheckRF
Check generated time seriescheckTS
Daily streamflow data datadisch
Autocorrelation structure fittingfitACS
Fit the AutoCorrelation Transformation Functionfitactf
Distribution fittingfitDist
VAR model parameters to simulate correlated parent Gaussian random vectors and fieldsfitVAR
Simulation of multiple time series with given marginals and spatiotemporal propertiesgenerateMTS
Faster simulation of multiple time series with approximately separable spatiotemporal correlation structuregenerateMTSFast
Simulation of random fields with given marginals and spatiotemporal propertiesgenerateRF
Faster simulation of random fields with approximately separable spatiotemporal correlation structuregenerateRFFast
Generate time seriesgenerateTS
Generalized Extreme Value distributiondgev GEV mgev pgev qgev rgev
Generalized Gamma distributiondggamma GGamma mggamma pggamma qggamma rggamma
Numerical estimation of momentsmoments
Pareto Type II distributiondparetoII mparetoII ParetoII pparetoII qparetoII rparetoII
Plot method for 'acti' objectsplot.acti
Plot method for 'checkTS' objectsplot.checkTS
Plot method for 'cosmosts' objectsplot.cosmosts
Plot method for 'fitACS' objectsplot.fitACS
Plot method for 'fitDist' objectsplot.fitDist
Hourly station precipitation dataprecip
Quick visualisation of basic time series propertiesquickTSPlot
Bulk time series generationregenerateTS
Sample momentssample.moments
Clayton SpatioTemporal Correlation Structurestcfclayton
Gneiting-14 SpatioTemporal Correlation Structurestcfgneiting14
Gneiting-16 SpatioTemporal Correlation Structurestcfgneiting16
SpatioTemporal Correlation Structurestcs