All functions
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assim.batch()
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Run Batch PDA |
autoburnin()
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Automatically calculate and apply burnin value |
correlationPlot()
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Flexible function to create correlation density plots |
gelman_diag_gelmanPlot()
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Calculate Gelman Diagnostic using coda::gelman.plot |
gelman_diag_mw()
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Calculate Gelman diagnostic on moving window |
getBurnin()
|
Calculate burnin value |
load.L2Ameriflux.cf() load.pda.data()
|
Load Ameriflux L2 Data From NetCDF |
makeMCMCList()
|
Make MCMC list from samples list |
pda.adjust.jumps()
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Adjust PDA MCMC jump size |
pda.adjust.jumps.bs()
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Adjust PDA block MCMC jump size |
pda.autocorr.calc()
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autocorrelation correction |
pda.bayesian.tools()
|
Paramater Data Assimilation using BayesianTools |
pda.calc.error()
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Calculate sufficient statistics |
pda.calc.llik()
|
Calculate Likelihoods for PDA |
pda.calc.llik.par()
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pda.calc.llik.par |
pda.create.btprior()
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Create priors for BayesianTools |
pda.create.ensemble()
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Create ensemble record for PDA ensemble |
pda.define.llik.fn()
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Define PDA Likelihood Functions |
pda.define.prior.fn()
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Define PDA Prior Functions |
pda.emulator()
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Paramater Data Assimilation using emulator |
pda.generate.knots()
|
Generate Parameter Knots for PDA Emulator |
pda.generate.sf()
|
Generate scaling factor knots for PDA Emulator |
pda.get.model.output()
|
Get Model Output for PDA |
pda.init.params()
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Initialise Parameter Matrix for PDA |
pda.init.run()
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Initialise Model Runs for PDA |
pda.load.priors()
|
Load Priors for Paramater Data Assimilation |
pda.mcmc()
|
Paramater Data Assimilation using MCMC |
pda.mcmc.bs()
|
Paramater Data Assimilation using MCMC |
pda.mcmc.recover()
|
Clean up a failed PDA run |
pda.neff.calc()
|
Calculate N_eff |
pda.plot.params()
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Plot PDA Parameter Diagnostics |
pda.postprocess()
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Postprocessing for PDA Results |
pda.settings()
|
Set PDA Settings |
pda.settings.bt()
|
Apply settings for BayesianTools |
return.bias()
|
return.bias |
return_hyperpars()
|
return_hyperpars |
sample_MCMC()
|
Helper function to sample from previous MCMC chain while proposing new knots |
write_sf_posterior()
|
Function to write posterior distributions of the scaling factors |