mcmc-0.6.2.5: Sample from a posterior using Markov chain Monte Carlo

Index - S

sAnalysisNameMcmc.Settings, Mcmc
SaveMcmc.Settings, Mcmc
savedAcceptanceMcmc.Chain.Save
SavedChain 
1 (Type/Class)Mcmc.Chain.Save
2 (Data Constructor)Mcmc.Chain.Save
savedIdMcmc.Chain.Save
savedIterationMcmc.Chain.Save
savedLinkMcmc.Chain.Save
savedSeedMcmc.Chain.Save
savedTraceMcmc.Chain.Save
savedTuningParametersMcmc.Chain.Save
SaveModeMcmc.Settings, Mcmc
sBurnInMcmc.Settings, Mcmc
ScaleMcmc.Statistics.Types, Mcmc
scaleMcmc.Proposal.Scale, Mcmc
scaleBactrianMcmc.Proposal.Bactrian, Mcmc
scaleContrarilyMcmc.Proposal.Scale, Mcmc
scaleUnbiasedMcmc.Proposal.Scale, Mcmc
SequentialMcmc.Settings, Mcmc
SequentialOMcmc.Cycle, Mcmc
SequentialReversibleOMcmc.Cycle, Mcmc
setOrderMcmc.Cycle, Mcmc
Settings 
1 (Type/Class)Mcmc.Settings, Mcmc
2 (Data Constructor)Mcmc.Settings, Mcmc
settingsMcmc.Environment
settingsCheckMcmc.Settings, Mcmc
settingsLoadMcmc.Settings, Mcmc
settingsPrettyPrintMcmc.Settings, Mcmc
settingsSaveMcmc.Settings, Mcmc
sExecutionModeMcmc.Settings, Mcmc
ShapeMcmc.Statistics.Types, Mcmc
simpleMonitorMcmc.Monitor, Mcmc
SimplexMcmc.Proposal.Simplex, Mcmc
simplexFromVectorMcmc.Proposal.Simplex, Mcmc
simplexUniformMcmc.Proposal.Simplex, Mcmc
sIterationsMcmc.Settings, Mcmc
SizeMcmc.Statistics.Types, Mcmc
slideMcmc.Proposal.Slide, Mcmc
slideBactrianMcmc.Proposal.Bactrian, Mcmc
slideContrarilyMcmc.Proposal.Slide, Mcmc
slideSymmetricMcmc.Proposal.Slide, Mcmc
slideUniformSymmetricMcmc.Proposal.Slide, Mcmc
sLogModeMcmc.Settings, Mcmc
sParallelizationModeMcmc.Settings, Mcmc
SpikeParameterMcmc.Proposal.Bactrian
sSaveModeMcmc.Settings, Mcmc
StandardDeviationMcmc.Statistics.Types, Mcmc
startMcmc.Chain.Chain
startingTimeMcmc.Environment
stateMcmc.Chain.Link
SteppingStoneSamplingMcmc.MarginalLikelihood, Mcmc
sTraceLengthMcmc.Settings, Mcmc
summarizeCycleMcmc.Cycle
summarizeProposalMcmc.Proposal
sVerbosityMcmc.Settings, Mcmc
SwapPeriod 
1 (Type/Class)Mcmc.Algorithm.MC3, Mcmc
2 (Data Constructor)Mcmc.Algorithm.MC3, Mcmc