General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics

AdaptpCR | Adapts pCR values |

AM | The Adaptive Metropolis Algorithm |

applySettingsDefault | Provides the default settings for the different samplers in... |

BayesianTools | BayesianTools |

betaFun | Helper function for calculating beta |

bridgesample | Calculates the marginal likelihood of a chain via bridge... |

checkBayesianSetup | Checks if an object is of class 'BayesianSetup' |

combineChains | Function to combine chains |

convertCoda | Convert coda::mcmc objects to BayesianTools::mcmcSampler |

correctThin | Checks if thin is conistent with nTotalSamples samples and if... |

correlationPlot | Flexible function to create correlation density plots |

createBayesianSetup | Creates a standardized collection of prior, likelihood and... |

createBetaPrior | Convenience function to create a beta prior |

createLikelihood | Creates a standardized likelihood class#' |

createMcmcSamplerList | Convenience function to create an object of class... |

createPosterior | Creates a standardized posterior class |

createPrior | Creates a standardized prior class |

createPriorDensity | Fits a density function to a multivariate sample |

createProposalGenerator | Factory that creates a proposal generator |

createSmcSamplerList | Convenience function to create an object of class... |

createTruncatedNormalPrior | Convenience function to create a truncated normal prior |

createUniformPrior | Convenience function to create a simple uniform prior... |

DE | Differential-Evolution MCMC |

DEzs | Differential-Evolution MCMC zs |

DIC | Deviance information criterion |

DR | The Delayed Rejection Algorithm |

DRAM | The Delayed Rejection Adaptive Metropolis Algorithm |

DREAM | DREAM |

DREAMzs | DREAMzs |

factorMatrice | factorMatrice |

gelmanDiagnostics | Runs Gelman Diagnotics over an BayesianOutput |

generateCRvalues | Generates matrix of CR values based on pCR |

generateParallelExecuter | Factory to generate a parallel executer of an existing... |

generateTestDensityMultiNormal | Multivariate normal likelihood |

getBlock | Determine the parameters in the block update |

getBlockSettings | getblockSettings |

getCredibleIntervals | Calculate confidence region from an MCMC or similar sample |

getDharmaResiduals | Creates a DHARMa object |

getMetropolisDefaultSettings | Returns Metropolis default settings |

getPanels | Calculates the panel combination for par(mfrow = ) |

getPossibleSamplerTypes | Returns possible sampler types |

getPredictiveDistribution | Calculates predictive distribution based on the parameters |

getPredictiveIntervals | Calculates Bayesian credible (confidence) and predictive... |

getRmvnorm | Produce multivariate normal proposal |

getSample | Extracts the sample from a bayesianOutput |

getSetup | Function to get the setup from a bayesianOutput |

getVolume | Calculate posterior volume |

Gfun | Helper function for blow and hop moves |

GOF | Standard GOF metrics Startvalues for sampling with nrChains >... |

likelihoodAR1 | AR1 type likelihood function |

likelihoodIidNormal | Normal / Gaussian Likelihood function |

logSumExp | Funktion to compute log(sum(exp(x)) |

M | The Metropolis Algorithm |

makeObjectClassCodaMCMC | Helper function to change an object to a coda mcmc class, |

MAP | calculates the Maxiumum APosteriori value (MAP) |

marginalLikelihood | Calcluated the marginal likelihood from a set of MCMC samples |

marginalPlot | Plot MCMC marginals |

marginalPlotDensity | Plot marginals as densities |

marginalPlotViolin | Plot marginals as violin plot |

mcmcMultipleChains | Run multiple chains |

Metropolis | Creates a Metropolis-type MCMC with options for covariance... |

metropolisRatio | Function to calculate the metropolis ratio |

package-deprecated | Allows to mix a given parameter vector with a default... |

plotDiagnostic | Diagnostic Plot |

plotSensitivity | Performs a one-factor-at-a-time sensitivity analysis for the... |

plotTimeSeries | Plots a time series, with the option to include confidence... |

plotTimeSeriesResiduals | Plots residuals of a time series |

plotTimeSeriesResults | Creates a time series plot typical for an MCMC / SMC fit |

propFun | Helper function to create proposal |

rescale | Rescale |

runMCMC | Main wrapper function to start MCMCs, particle MCMCs and SMCs |

sampleEquallySpaced | Gets n equally spaced samples (rows) from a matrix or vector |

sampleMetropolis | gets samples while adopting the MCMC proposal generator |

scaleMatrix | Function to scale matrices |

setupStartProposal | Help function to find starvalues and proposalGenerator... |

smcSampler | SMC sampler |

stopParallel | Function to close cluster in BayesianSetup |

sumSquare | Helper function for sum of x*x |

testDensityBanana | Banana-shaped density function |

testDensityInfinity | Test function infinity ragged |

testDensityMultiNormal | 3d Mutivariate Normal likelihood |

testDensityNormal | Normal likelihood |

testLinearModel | Fake model, returns a ax + b linear response to 2-param... |

thinMatrix | Function to thin matrices |

tracePlot | Trace plot for MCMC class |

Twalk | T-walk MCMC |

TwalkMove | Wrapper for step function |

Twalksteps | Main function that is executing and evaluating the moves |

updateGroups | Determine the groups of correlated parameters |

updateProposalGenerator | To update settings of an existing proposal genenerator |

VSEM | Very simple ecosystem model |

vsemC | C version of the VSEM model |

VSEMcreateLikelihood | Create an example dataset, and from that a likelihood or... |

VSEMcreatePAR | Create a random radiation (PAR) time series |

VSEMgetDefaults | returns the default values for the VSEM |

WAIC | calculates the WAIC |

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