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PAWL (version 0.5)
Implementation of the PAWL algorithm
Description
Implementation of the Parallel Adaptive Wang-Landau algorithm. Also implemented for comparison: parallel adaptive Metropolis-Hastings,SMC sampler.
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Version
Version
0.5
0.3
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Install
install.packages('PAWL')
Monthly Downloads
20
Version
0.5
License
GPL (>= 2)
Maintainer
Pierre Jacob
Last Published
November 15th, 2012
Functions in PAWL (0.5)
Search functions
tuningparameters
MCMC Tuning Parameters
PlotFH
Plot of the Flat Histogram occurrences
PlotHist
Plot a histogram of one component of the chains
PlotNbins
Plot of the increase of the number of bins along the iterations
PAWL-package
PARALLEL ADAPTIVE WANG-LANDAU
createAdaptiveRandomWalkProposal
Adaptive Random Walk proposal distribution for MCMC algorithms
binning
Class
"binning"
createTrimodalTarget
Trimodal target distribution
normalizeweight
Normalize weights
ConvertResults
Convert Results
smcparameters
SMC Tuning Parameters
proposal
Class
"proposal"
PlotAllVar
Trace plot of all the variables
preexplorationAMH
Pre exploration Adapative Metropolis-Hastings
target
Class: target distribution
IceFloe
Image of ice floes
Pollution
Pollution Data
adaptiveMH
Adaptive Metropolis-Hastings
pawl
Parallel Adaptive Wang-Landau
PlotComp1vsComp2
Plot one component versus another in a scatter plot
PlotLogTheta
Plot of the log theta penalties
createMixtureTarget
Mixture target distribution
smc
Sequential Monte Carlo
PlotHistBin
Plot a histogram of the binning coordinate
getFrequencies
Observed Frequencies in each bin.
PlotDensComp1vsComp2
Plot one component versus another in a density plot