Implementation of the PAWL algorithm


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Documentation for package ‘PAWL’ version 0.5

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PAWL-package PARALLEL ADAPTIVE WANG-LANDAU
adaptiveMH Adaptive Metropolis-Hastings
binning Class '"binning"'
binning-class Class '"binning"'
binning-method Class '"binning"'
binning-methods Class '"binning"'
ConvertResults Convert Results
createAdaptiveRandomWalkProposal Adaptive Random Walk proposal distribution for MCMC algorithms
createMixtureTarget Mixture target distribution
createTrimodalTarget Trimodal target distribution
getFrequencies Observed Frequencies in each bin.
IceFloe Image of ice floes
icefloe Image of ice floes
normalizeweight Normalize weights
PAWL PARALLEL ADAPTIVE WANG-LANDAU
pawl Parallel Adaptive Wang-Landau
PlotAllVar Trace plot of all the variables
PlotComp1vsComp2 Plot one component versus another in a scatter plot
PlotDensComp1vsComp2 Plot one component versus another in a density plot
PlotFH Plot of the Flat Histogram occurrences
PlotHist Plot a histogram of one component of the chains
PlotHistBin Plot a histogram of the binning coordinate
PlotLogTheta Plot of the log theta penalties
PlotNbins Plot of the increase of the number of bins along the iterations
Pollution Pollution Data
pollution Pollution Data
preexplorationAMH Pre exploration Adapative Metropolis-Hastings
proposal Class '"proposal"'
proposal-class Class '"proposal"'
proposal-method Class '"proposal"'
show-method Class '"binning"'
show-method Class '"proposal"'
show-method SMC Tuning Parameters
show-method Class: target distribution
show-method MCMC Tuning Parameters
smc Sequential Monte Carlo
smcparameters SMC Tuning Parameters
smcparameters-class SMC Tuning Parameters
smcparameters-method SMC Tuning Parameters
target Class: target distribution
target-class Class: target distribution
target-method Class: target distribution
tuningparameters MCMC Tuning Parameters
tuningparameters-class MCMC Tuning Parameters
tuningparameters-method MCMC Tuning Parameters