Man pages for rjbgoudie/structmcmc
Structural inference for Bayesian Networks and Variable Selection.

adjustPredictionsAdjust the predictions
allBannedExceptPPNotBannedIfNotRequiredMake a banned list.
allDescendantsGet descendants of all nodes.
allNonDescendantsGet non-descendants of all nodes. epmx to a data.frame
as.grainConvert to grain.
as.rocPrepare data for plotting in a ROC plot.
as.roc.epPrepare an edge probability matrix for a ROC plot.
as.roc.ep.listPrepare an list of edge probability matrix for a ROC plot.
as.roc.parentalPrepare a parental for a ROC plot.
as.roc.parental.listPrepare a parental list for a ROC plot.
aurocCompute the area under an ROC curve.
auroc.epCompute the area under an ROC curve.
auroc.ep.listCompute the area under an ROC curve.
bayesBayesian posterior parameter estimates.
bayes.bnBayesian posterior parameter estimates.
bfBayes Factor.
bf.bnpostmcmcBayes Factors.
BNGibbsSamplerGibbs sampler for Bayesian Networks.
BNOrderSamplerOrder MCMC sampler for Bayesian Networks.
bnpostBN Exact Posterior.
bnpostmcmcBN Posterior from MCMC.
bnpostmcmc.listList of BN Posteriors from MCMC.
BNSamplerCreate a MCMC sampler (MC^3) for Bayesian Networks.
BNSamplerBigFlipsBig flips MCMC sampler for Bayesian networks.
BNSamplerMJMode-jumping MCMC sampler for Bayesian Networks.
burninExtract burnin
burnin.samplerExtract burnin
checkForNonDuplicatedRemove options that don't duplicate required duplicates.
convertEPMatrixToColumnsConvert edge prob matrix to a column matrix
cumepCumulative edge probabilities.
cumep.bnpostmcmc.listCumulative edge probabilities.
cumep.samplersCumulative edge probabilities.
cummeanCumulative mean.
cummean.matrixCumulative mean.
cumtvdCumulative total variation distance.
cumtvd.listList of cumulative total variation distance.
dagGivenOrderSample a DAG given an order (weighted)
decimFind the non-integer part of a number
defaultBannedMaximal banned list.
dotplot.epDotplot of posterior edge probabilities.
dotplot.ep.listDotplot of list of posterior edge probabilities.
dotplot.gpDotplot of posterior graph probabilities. of posterior graph probabilities.
drawDraw samples from a MCMC sampler.
drawSamplesByStepCountDraw samples from a MCMC sampler, by step count.
drawSamplesByTimeDraw samples from a MCMC sampler, by time.
eachChangesChoicesForRequiredEach changes choices for required.
edgeIsFlippableFind flippable edges.
ehtExpected hitting time.
eht.bnpostExpected hitting time.
enumerateParentsTableTable of all possible parents of a node.
enumerateParentsTableNodeTable of all possible parents of a node.
epPosterior edge probabilities.
ep.bnpostPosterior edge probabilities.
ep.bnpostmcmcPosterior edge probabiities.
ep.bnpostmcmc.listPosterior edge probabilities.
ep.listList of posterior edge probabilities.
epmxEdge probabilties matrix.
epmx.bnpostmcmcEdge probabilities matrix.
epmx.bnpostmcmc.listEdge probabilities matrix.
epmxPlotInternal(Internal) Plot of cumulative edge probabilities.
epmx.samplerEdge probabilities matrix from a sampler.
epmx.samplersEdge probabilities matrix.
ep.parental.contingencyPosterior edge probabilities.
ep.parental.listPosterior edge probabilities.
ep.samplerExtract posterior edge probabiities from a sampler.
ep.tableComputes the edge probabilities implied by a table.
eval.priorCompute prior score of a Bayesian network.
exactposteriorPosterior distribution on Bayesian networks.
fastidFast ID of a graph.
fdfAsIntConvert a data frame of factors to integers.
gelmanGelman and Rubin's convergence diagnostic
gelman.samplersGelman and Rubin's convergence diagnostic
getAllConsistentWithDAGGet all consistent with DAG
getBannedFromConstraintResample a pair of nodes together.
getNewGraphList graphs in change node neighbourhood.
getPossibleParentsGet possible parents.
getRequiredFromConstraintResample a pair of nodes together.
getRowsThatContainCreate lookup table for parentsTable.
gpPosterior graph probabilities.
gp.bnpostPosterior graph probaiblities.
gp.bnpostmcmcPosterior graph probabilities.
gp.bnpostmcmc.listPosterior graph probabilities.
gp.listList of posterior graph probabilities.
gp.samplerRetreive graph probabilities from sampler
graphProbGivenOrderProbability of a graph given an order.
hpHitting probability.
intAsFDFConvert a data frame of integers to factors.
internal-onloadInternal function.
intersect2Fast, dangerous set intersect.
intersectionMultiple intersection function
isConsistentWithOrderIs a BN consistent with an order?
is.valid.hypChecks validity.
is.valid.localPriorsCheck validity.
is.valid.priorCheck validity.
kronecker_deltaMetric: Kronecker delta
length.bnpostmcmcNumber of samples drawn.
length.samplerNumber of samples drawn.
levelplot.bnpostmcmcLevelplot of BN Posterior from MCMC.
levelplot.epLevelplot of posterior edge probabilities.
levelplot.ep.listLevelplot of posterior edge probabilities.
localLogScoreMultDirLocal Multinomial-Dirichlet Log marginal likelihood.
localLogScoreNormalLocal Normal-inverse-gamma (with g-prior) Log marginal...
logNumMHNeighbours(Log) Number of neighbouring networks.
logOrderLikelihoodLog likelihood of an order
logScoreMultDirMultinomial-Dirichlet Log marginal likelihood.
logScoreMultDir.bnCompute the log marginal likelihood of the supplied Bayesian... Log marginal likelihood.
logScoreMultDir.bnpostmcmcLog scores of best graphs.
logScoreMultDirFUNMultinomial-Dirichlet Log marginal likelihood.
logScoreMultDirIncrementalMultinomial-Dirichlet Log marginal likelihood (online).
logScoreMultDirOfflineMultinomial-Dirichlet Log marginal likelihood (offline).
logScoreMultDirPrepareInternal functions.
logScoreNormalNormal-inverse-gamma (with g-prior) Log marginal likelihood.
logScoreNormal.bnNormal-inverse-gamma (with g-prior) Log marginal likelihood. (with g-prior) Log marginal likelihood.
logScoreNormalFUNNormal Log marginal likelihood.
logScoreNormalIncrementalNormal-inverse-gamma (with g-prior) Log marginal likelihood...
logScoreNormalOfflineNormal-inverse-gamma (with g-prior) Log marginal likelihood...
logScoreNormalPrepareInternal functions.
makeRowPredictionsMake row predictions
mapMaximum aposteriori graph.
map.bnpostMaximum aposteriori graph.
map.bnpostmcmcMaximum aposteriori graph.
map.samplerRetreive MAP from sampler
marginalGivenInterventionGet marginal probabilities, given an intervention.
marginalGivenOthersGet all marginal probabilities.
matrix2Fast, dangerous matrix generation.
mcmcposteriorPosterior distribution on Bayesian networks.
mlMaximum likelihood estimates.
ml.bnMaximum likelihood estimates for parameters of a BN.
mukherjeeBioinformaticsPriorMukherjee Bioinformatics prior.
mwepMoving window edge probiilities.
mwep.bnpostmcmc.listMoving window edge probabilities.
mwep.samplersMoving window edge probabilities.
mwmeanMoving window mean.
mwmean.matrixMoving window mean.
new_queuePriority queue
new_stackMost-recently used stack.
nonDescendantsFind nonDescendants.
numberDAGsGivenOrderNumber of BNs consistent with an order.
nuniqueNumber of unique.
options.gridinput a list x.
orderFlipOperatorDraw order proposal using flip-operator
parentalFromEPThresholdThreshold posterior edge probabilities.
parentalToCPDAGConvert 'parental list' to CPDAGs.
plot.bnpostmcmcPlot top graphs.
plotTapePlot tape.
posteriorPosterior distribution on Bayesian networks.
predict.bnPredict a Multinomial-Dirichlet model
predictGivenNoParentsPredict a node, given no parents
predictGivenParentsPredict a node, given parents
predictModelAverageNodePredict a Multinomial-Dirichlet model
predictNodePredict a Multinomial-Dirichlet model
prepareGPPlotInternal function.
prepareLevelPlotInternal function.
print.samplerPrint a sampler
priorGraphA standard 'graph prior'.
priorUniformA uniform prior for graphs.
queryFindingQuery an independence network, given a finding.
removeDuplicatesRemove duplicates
requireSomethingFromEachParentRequire something from each parent.
residsNormalResiduals from a Normal model
residsNormalNodeResiduals for a single node for a Normal model
residualsMultDirResiduals from a Multinomial-Dirichlet model
residualsMultDirNodeResiduals for a single node for a Multinomial-Dirichlet model
rocplotPlot an ROC curve.
routesAddEdgesUpdate a routes matrix (edge addition).
routesRemoveEdgesUpdate a routes matrix (edge removal).
rowProbabiltiesToResponseGet prediction for a row
rowSums2Fast, dangerous row sums.
sampleNodeSample the parents of a single node (Gibbs sampler).
samplePairSample the parents of a pair of nodes (Gibbs sampler).
samplePair2Sample the parents of a pair of nodes (Gibbs sampler) v2.
sampleQuadrupleSample the parents of a quadruple of nodes (Gibbs sampler).
sampleQuintupleSample the parents of a quintuple of nodes (Gibbs sampler).
samplersList of MCMC Samplers
sampleTripleSample the parents of a triple of nodes (Gibbs sampler).
scoreParentsTableScore a node-level parentsTable.
scoreParentsTableNodeScore a node-level parentsTable.
setdiff3Fast, dangerous set difference.
setupConstraintSetup constraint.
shrinkepInternal function.
splom.bnpostmcmc.listScatterplot matrix of edge probabilities between runs.
splom.epmxPlot of cumulative edge probabilities.
square_errorMetric: Square error
statisticsExtract statistics from a sampler.
statistics.samplerExtract statistics from a sampler.
stepsNumber of samples drawn.
steps.samplerNumber of samples drawn.
structmcmcThe structmcmc package.
summary.gpSummary of posterior graph probabilities.
summary.samplerSummarising MCMC samplers
topTop posterior graph.
top.bnpostTop graph from BN Posterior.
top.bnpostmcmcTop graph from BN Posterior.
top.samplerRetreive top graph from sampler
topScoringGraphGet modal graph given an order.
tpTransition probabilities.
tp.bnpostTransition probabilities.
transposeEdgeIsAddableFind togglable edges.
transposeEdgeIsRemovableFind togglable edges.
transposeEdgeIsTogglableFind togglable edges.
validStartEndCheck validity of start and end.
whichGraphsNotNeighboursIdentify neighbouring graphs.
whichNumFind rows satisfying equality.
whichParentSetRowsFind relevants rows of a parentsTable.
xyplot.cumtvdPlot cumulative total variation distance.
xyplot.cumtvd.listPlot of cumulative total variation distance.
xyplot.epmxPlot of cumulative edge probabilities.
xyplot.gpScatterplot of posterior graph probabilities. of posterior graph probablities.
rjbgoudie/structmcmc documentation built on Sept. 2, 2017, 11:02 a.m.