Package: PEcAn.uncertainty 1.9.0.9000

David LeBauer

PEcAn.uncertainty: PEcAn Functions Used for Propagating and Partitioning Uncertainties in Ecological Forecasts and Reanalysis

The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PECAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation.

Authors:David LeBauer, Mike Dietze, Xiaohui Feng, Dan Wang, Carl Davidson, Rob Kooper, Shawn Serbin

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manual.pdf |manual.html✨
card.svg |card.png
PEcAn.uncertainty/json (API)
NEWS

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

Bug tracker:https://github.com/pecanproject/pecan/issues

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC - binary JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written with three aims in mind: * To have an engine for the BUGS language that runs on Unix * To be extensible, allowing users to write their own functions, distributions and samplers. * To be a plaftorm for experimentation with ideas in Bayesian modelling This package contains the 'jags' binary as well as the associated shared library modules loaded by the binary.
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

ecological-forecastingsensitivity-analysispecanuncertainty-propagationbayesiancyberinfrastructuredata-assimilationdata-scienceecosystem-modelecosystem-scienceforecastingmeta-analysisnational-science-foundationplantsjagscpp

9.40 score 236 stars 5 packages 28 scripts 35 exports 123 dependencies

Last updated from:a8448f44d6. Checks:7 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64WARNING169
source / vignettesOK240
linux-release-x86_64WARNING160
macos-release-arm64WARNING126
macos-oldrel-arm64WARNING113
windows-develWARNING96
windows-releaseWARNING99
windows-oldrelWARNING99
wasm-releaseOK121

Exports:compute_sobol_indicesensemble.filenameensemble.tsflux.uncertaintygenerate_joint_ensemble_designgenerate_OAT_SA_designget_parameter_samplesget.changeget.coef.varget.elasticityget.ensemble.samplesget.parameter.samplesget.resultsget.sensitivityinput.ens.genplot_flux_uncertaintyplot_sensitivitiesplot_sensitivityplot_variance_decompositionread.ameriflux.L2read.ensemble.outputread.ensemble.tsread.sa.outputrun.ensemble.analysisrun.sensitivity.analysisrunModule.get.resultsrunModule.run.ensemble.analysisrunModule.run.sensitivity.analysissa.splinefunsd.varsensitivity.analysissensitivity.filenamespline.truncatewrite.ensemble.configswrite.sa.configs

Dependencies:abindaskpassbase64encblobbootbslibcachemclasscliclueclustercodacodetoolscommonmarkcpp11curlDBIdbplyrdigestdplyrdtwdtwclustfarverfastmapflexclustfontawesomeforeachfsfurrrfuturegenericsggplot2ggrepelglobalsgluegridExtragtablehtmltoolshttpuvhttrisobanditeratorsjquerylibjsonlitelabelinglaterlatticelifecyclelistenvlubridatemagrittrMASSMatrixMatrixModelsmcmcMCMCpackmemoisemimemodeltoolsmvtnormncdf4numbersopenssloptparseotelparallellyPEcAn.DBPEcAn.emulatorPEcAn.loggerPEcAn.MAPEcAn.priorsPEcAn.remotePEcAn.settingsPEcAn.utilspillarpkgconfigplyrpromisesproxypurrrquantregR.methodsS3R.ooR.utilsR6randtoolboxrappdirsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelRcppThreadreshape2rjagsrlangrngWELLRSpectraS7sassscalessensitivityshinyshinyjssourcetoolsSparseMstringistringrsurvivalsystibbletidyrtidyselecttimechangetriebeardunitsurltoolsutf8vctrsviridisLitewithrXMLxtable

Readme and manuals

Help Manual

Help pageTopics
Compute Sobol indices from a finished PEcAn runcompute_sobol_indices
Generate ensemble filenamesensemble.filename
Plots an ensemble time-series from PEcAn for the selected target variableensemble.ts
Calculate parameters for heteroskedastic flux uncertaintyflux.uncertainty
Generate joint ensemble design for parameter sampling Creates a joint ensemble design that maintains parameter correlations across all sites in a multi-site run. This function generates sample indices that are shared across sites to ensure consistent parameter sampling.generate_joint_ensemble_design
Generate One-At-a-Time (OAT) input design for sensitivity analysisgenerate_OAT_SA_design
Generate parameter samples from priors and MCMC posteriors (pure function)get_parameter_samples
Get delta between sequential flux datapointsget.change
Get coefficient of varianceget.coef.var
Generic function for the elasticityget.elasticity
Get parameter values used in ensembleget.ensemble.samples
Get g_i(phi_i)get.gi.phii
Convert priors / MCMC samples to parameter sample chainsget.parameter.samples
Read model output and save parsed results for sensitivity and ensemble analysesget.results
Calculate the sensitivity of a function at the medianget.sensitivity
Generate an ensemble of samples from one inputinput.ens.gen
Calculates the excess kurtosis of a vectorkurtosis
Plot fit for heteroskedastic flux uncertaintyplot_flux_uncertainty
Plot functions and quantiles used in sensitivity analysisplot_sensitivities
Sensitivity plotplot_sensitivity
Variance Decomposition Plotsplot_variance_decomposition
Read Ameriflux L2 Dataread.ameriflux.L2
Reads output from model ensembleread.ensemble.output
Reads ensemble time-series from PEcAn for the selected target variableread.ensemble.ts
Reads output of sensitivity analysis runsread.sa.output
Run ensemble analysis on finished model runsrun.ensemble.analysis
Run sensitivity analysis on finished model runsrun.sensitivity.analysis
Apply get.results to each of a list of settingsrunModule.get.results
Run ensemble analyses across all sites in settingsrunModule.run.ensemble.analysis
Run sensitivity analysis for every Settings in a MultiSettingsrunModule.run.sensitivity.analysis
Spline estimate of univariate relationship between parameter value and model outputsa.splinefun
Calculates the standard deviation of the variance estimatesd.var
Performs univariate sensitivity analysis and variance decompositionsensitivity.analysis
Generate sensitivity analysis filenamessensitivity.filename
Spline Ensemblespline.ensemble
Truncate spline at zero if...spline.truncate
variance statisticsvariance.stats
Write ensemble config fileswrite.ensemble.configs
Write sensitivity analysis config fileswrite.sa.configs