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BayesianTools (version 0.1.7)

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

Description

General-purpose MCMC and SMC samplers, as well as plot and diagnostic functions for Bayesian statistics, with a particular focus on calibrating complex system models. Implemented samplers include various Metropolis MCMC variants (including adaptive and/or delayed rejection MH), the T-walk, two differential evolution MCMCs, two DREAM MCMCs, and a sequential Monte Carlo (SMC) particle filter.

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Install

install.packages('BayesianTools')

Monthly Downloads

978

Version

0.1.7

License

GPL-3

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Repository

https://github.com/florianhartig/BayesianTools

Maintainer

Florian Hartig

Last Published

December 9th, 2019

Functions in BayesianTools (0.1.7)

Adapts pCR values

createPriorDensity

Fits a density function to a multivariate sample

Helper function for calculating beta

Deviance information criterion

Differential-Evolution MCMC zs

Determine the parameters in the block update

Differential-Evolution MCMC

Convert coda::mcmc objects to BayesianTools::mcmcSampler

Very simple ecosystem model

createProposalGenerator

Factory that creates a proposal generator

VSEMcreateLikelihood

Create an example dataset, and from that a likelihood or posterior for the VSEM model

Create a random radiation (PAR) time series

Wrapper for step function

createBetaPrior

Convenience function to create a beta prior

Standard GOF metrics Startvalues for sampling with nrChains > 1 : if you want to provide different start values for the different chains, provide a list

The Delayed Rejection Algorithm

getPredictiveIntervals

Calculates Bayesian credible (confidence) and predictive intervals based on parameter sample

Main function that is executing and evaluating the moves

The Metropolis Algorithm

calculates the Maxiumum APosteriori value (MAP)

getMetropolisDefaultSettings

Returns Metropolis default settings

Calculates the marginal likelihood of a chain via bridge sampling

createUniformPrior

Convenience function to create a simple uniform prior distribution

Produce multivariate normal proposal

setupStartProposal

Help function to find starvalues and proposalGenerator settings

Calculate posterior volume

Helper function for blow and hop moves

The Delayed Rejection Adaptive Metropolis Algorithm

Function to combine chains

createPosterior

Creates a standardized posterior class

VSEMgetDefaults

returns the default values for the VSEM

Creates a Metropolis-type MCMC with options for covariance adaptatin, delayed rejection, Metropolis-within-Gibbs, and tempering

Calculates the panel combination for par(mfrow = )

gelmanDiagnostics

Runs Gelman Diagnotics over an BayesianOutput

createMcmcSamplerList

Convenience function to create an object of class mcmcSamplerList from a list of mcmc samplers

createLikelihood

Creates a standardized likelihood class#'

Helper function to create proposal

generateCRvalues

Generates matrix of CR values based on pCR

testDensityNormal

Normal likelihood

AR1 type likelihood function

createMixWithDefaults

Allows to mix a given parameter vector with a default parameter vector

Function to scale matrices

sampleMetropolis

gets samples while adopting the MCMC proposal generator

checkBayesianSetup

Checks if an object is of class 'BayesianSetup'

calibrationTest

Simulation-based calibration tests

testDensityBanana

Banana-shaped density function

testDensityMultiNormal

3d Mutivariate Normal likelihood

Diagnostic Plot

Creates a standardized prior class

generateParallelExecuter

Factory to generate a parallel executer of an existing function

Extracts the sample from a bayesianOutput

marginalPlotViolin

Plot marginals as violin plot

mcmcMultipleChains

Run multiple chains

getDharmaResiduals

Creates a DHARMa object

getBlockSettings

getblockSettings

plotTimeSeriesResiduals

Plots residuals of a time series

createTruncatedNormalPrior

Convenience function to create a truncated normal prior

generateTestDensityMultiNormal

Multivariate normal likelihood

testLinearModel

Fake model, returns a ax + b linear response to 2-param vector

plotSensitivity

Performs a one-factor-at-a-time sensitivity analysis for the posterior of a given bayesianSetup within the prior range.

marginalLikelihood

Calcluated the marginal likelihood from a set of MCMC samples

Plots a time series, with the option to include confidence and prediction band

makeObjectClassCodaMCMC

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

testDensityInfinity

Test function infinity ragged

createBayesianSetup

Creates a standardized collection of prior, likelihood and posterior functions, including error checks etc.

getPredictiveDistribution

Calculates predictive distribution based on the parameters

Function to close cluster in BayesianSetup

Plot MCMC marginals

marginalPlotDensity

Plot marginals as densities

plotTimeSeriesResults

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

getPossibleSamplerTypes

Returns possible sampler types

Function to thin matrices

Trace plot for MCMC class

Determine the groups of correlated parameters

Helper function for sum of x*x

applySettingsDefault

Provides the default settings for the different samplers in runMCMC

correlationPlot

Flexible function to create correlation density plots

calculates the WAIC

Checks if thin is conistent with nTotalSamples samples and if not corrects it.

Main wrapper function to start MCMCs, particle MCMCs and SMCs

createSmcSamplerList

Convenience function to create an object of class SMCSamplerList from a list of mcmc samplers

likelihoodIidNormal

Normal / Gaussian Likelihood function

updateProposalGenerator

To update settings of an existing proposal genenerator

C version of the VSEM model

metropolisRatio

Function to calculate the metropolis ratio

Function to get the setup from a bayesianOutput

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

sampleEquallySpaced

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

The Adaptive Metropolis Algorithm

getCredibleIntervals

Calculate confidence region from an MCMC or similar sample