Package: bnstruct 1.0.15
bnstruct: Bayesian Network Structure Learning from Data with Missing Values
Bayesian Network Structure Learning from Data with Missing Values. The package implements the Silander-Myllymaki complete search, the Max-Min Parents-and-Children, the Hill-Climbing, the Max-Min Hill-climbing heuristic searches, and the Structural Expectation-Maximization algorithm. Available scoring functions are BDeu, AIC, BIC. The package also implements methods for generating and using bootstrap samples, imputed data, inference.
Authors:
bnstruct_1.0.15.tar.gz
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bnstruct_1.0.15.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
bnstruct/json (API)
| # Install 'bnstruct' in R: |
| install.packages('bnstruct', repos = c('https://albertofranzin.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- asia_10000 - 'Asia' dataset.
- asia_2_layers - Load a two-layers dataset derived from the 'Asia' dataset.
- child_NA_5000 - 'Child' dataset.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:7509d30a24. Checks:15 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 169 | ||
| linux-devel-x86_64 | OK | 219 | ||
| source / vignettes | OK | 200 | ||
| linux-release-arm64 | OK | 124 | ||
| linux-release-x86_64 | OK | 160 | ||
| macos-release-arm64 | OK | 192 | ||
| macos-release-x86_64 | OK | 379 | ||
| macos-oldrel-arm64 | OK | 196 | ||
| macos-oldrel-x86_64 | OK | 421 | ||
| windows-devel-arm64 | OK | 343 | ||
| windows-devel-x86_64 | OK | 143 | ||
| windows-release-arm64 | OK | 351 | ||
| windows-release-x86_64 | OK | 115 | ||
| windows-oldrel-x86_64 | OK | 99 | ||
| wasm-release | OK | 116 |
Exports:add.observations<-asiaasia_2_layersbelief.propagationbnBNbn<-BNDatasetbootbootsboots<-bootstrapbuild.junction.treechildcompletecptscpts<-dagdag.to.cpdagdag<-data.filedata.file<-discretenessdiscreteness<-edge.dir.wpdagemget.most.probable.valueshas.bootshas.imputed.bootshas.imputed.datahas.raw.dataheader.fileheader.file<-imp.bootsimp.boots<-imputeimputed.dataimputed.data<-InferenceEngineinterventionsjptsjpts<-jt.cliquesjt.cliques<-junction.treejunction.tree<-knn.imputelayeringlearn.dynamic.networklearn.networklearn.paramslearn.structuremarginalsnamename<-node.sizesnode.sizes<-num.bootsnum.boots<-num.itemsnum.items<-num.nodesnum.nodes<-num.time.stepsnum.time.steps<-num.variablesnum.variables<-observationsobservations<-quantilesquantiles<-raw.dataraw.data<-read.bifread.datasetread.dscread.netsample.datasetsample.rowsave.to.epsscoring.funcscoring.func<-shdshowstruct.algostruct.algo<-test.updated.bntune.knn.imputeupdated.bnupdated.bn<-variablesvariables<-wpdagwpdag.from.dagwpdag<-write_xgmmlwrite.dsc
Dependencies:bitopsclicpp11glueigraphlatticelifecyclemagrittrMatrixpkgconfigrlangvctrs
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| add further evidence to an existing list of observations of an 'InferenceEngine'. | add.observations<- add.observations<-,InferenceEngine-method |
| load 'Asia' dataset. | asia |
| 'Asia' dataset. | asia_10000 |
| load a two-layers dataset derived from the 'Asia' dataset. | asia_2_layers |
| perform belief propagation. | belief.propagation belief.propagation,InferenceEngine belief.propagation,InferenceEngine-method |
| get the 'BN' object contained in an 'InferenceEngine'. | bn bn,InferenceEngine bn,InferenceEngine-method |
| BN class definition. | BN BN,BN-class BN-class initialize,BN-method |
| set the original 'BN' object contained in an 'InferenceEngine'. | bn<- bn<-,InferenceEngine-method |
| BNDataset class. | BNDataset BNDataset,BNDataset-class BNDataset-class initialize,BNDataset-method |
| get selected element of bootstrap list. | boot boot,BNDataset boot,BNDataset,numeric-method |
| get list of bootstrap samples of a 'BNDataset'. | boots boots,BNDataset boots,BNDataset-method |
| set list of bootstrap samples of a 'BNDataset'. | boots<- boots<-,BNDataset-method |
| Perform bootstrap. | bootstrap bootstrap,BNDataset bootstrap,BNDataset-method |
| build a JunctionTree. | build.junction.tree build.junction.tree,InferenceEngine build.junction.tree,InferenceEngine-method |
| load 'Child' dataset. | child |
| 'Child' dataset. | child_NA_5000 |
| Subset a 'BNDataset' to get only complete cases. | complete complete,BNDataset complete,BNDataset-method |
| get the list of conditional probability tables of a 'BN'. | cpts cpts,BN cpts,BN-method |
| set the list of conditional probability tables of a network. | cpts<- cpts<-,BN-method |
| get adjacency matrix of a network. | dag dag,BN dag,BN-method |
| convert a DAG to a CPDAG | dag.to.cpdag |
| set adjacency matrix of an object. | dag<- dag<-,BN-method |
| get data file of a 'BNDataset'. | data.file data.file,BNDataset data.file,BNDataset-method |
| set data file of a 'BNDataset'. | data.file<- data.file<-,BNDataset-method |
| get status (discrete or continuous) of the variables of an object. | discreteness discreteness,BN discreteness,BN-method discreteness,BNDataset discreteness,BNDataset-method |
| set status (discrete or continuous) of the variables of an object. | discreteness<- discreteness<-,BN-method discreteness<-,BNDataset-method |
| counts the edges in a WPDAG with their directionality | edge.dir.wpdag |
| expectation-maximization algorithm. | em em,InferenceEngine,BNDataset em,InferenceEngine,BNDataset-method |
| compute the most probable values to be observed. | get.most.probable.values get.most.probable.values,BN get.most.probable.values,BN-method get.most.probable.values,InferenceEngine get.most.probable.values,InferenceEngine-method |
| check whether a 'BNDataset' has bootstrap samples or not. | has.boots has.boots,BNDataset has.boots,BNDataset-method |
| check whether a 'BNDataset' has bootstrap samples from imputed data or not. | has.imputed.boots has.imputed.boots,BNDataset has.imputed.boots,BNDataset-method |
| check if a BNDataset contains impited data. | has.imputed.data has.imputed.data,BNDataset has.imputed.data,BNDataset-method |
| check if a BNDataset contains raw data. | has.raw.data has.raw.data,BNDataset has.raw.data,BNDataset-method |
| get header file of a 'BNDataset'. | header.file header.file,BNDataset header.file,BNDataset-method |
| set header file of a 'BNDataset'. | header.file<- header.file<-,BNDataset-method |
| get list of bootstrap samples from imputed data of a 'BNDataset'. | imp.boots imp.boots,BNDataset imp.boots,BNDataset-method |
| set list of bootstrap samples from imputed data of a 'BNDataset'. | imp.boots<- imp.boots<-,BNDataset-method |
| Impute a 'BNDataset' raw data with missing values. | impute impute,BNDataset impute,BNDataset-method |
| get imputed data of a BNDataset. | imputed.data imputed.data,BNDataset imputed.data,BNDataset-method |
| add imputed data. | imputed.data<- imputed.data<-,BNDataset-method |
| InferenceEngine class. | InferenceEngine InferenceEngine,InferenceEngine-class InferenceEngine-class initialize,InferenceEngine-method |
| get the list of interventions of an 'InferenceEngine'. | interventions interventions,InferenceEngine interventions,InferenceEngine-method |
| set the list of interventions for an 'InferenceEngine'. | interventions<- interventions<-,InferenceEngine-method |
| get the list of joint probability tables compiled by an 'InferenceEngine'. | jpts jpts,InferenceEngine jpts,InferenceEngine-method |
| set the list of joint probability tables compiled by an 'InferenceEngine'. | jpts<- jpts<-,InferenceEngine-method |
| get the list of cliques of the junction tree of an 'InferenceEngine'. | jt.cliques jt.cliques,InferenceEngine jt.cliques,InferenceEngine-method |
| set the list of cliques of the junction tree of an 'InferenceEngine'. | jt.cliques<- jt.cliques<-,InferenceEngine-method |
| get the junction tree of an 'InferenceEngine'. | junction.tree junction.tree,InferenceEngine junction.tree,InferenceEngine-method |
| set the junction tree of an 'InferenceEngine'. | junction.tree<- junction.tree<-,InferenceEngine-method |
| Perform imputation of a data frame using k-NN. | knn.impute |
| return the layering of the nodes. | layering layering,BN layering,BN-method |
| learn a dynamic network (structure and parameters) of a BN from a BNDataset. | learn.dynamic.network learn.dynamic.network,BN learn.dynamic.network,BN-method learn.dynamic.network,BNDataset learn.dynamic.network,BNDataset-method |
| learn a network (structure and parameters) of a BN from a BNDataset. | learn.network learn.network,BN learn.network,BN-method learn.network,BNDataset learn.network,BNDataset-method |
| learn the parameters of a BN. | learn.params learn.params,BN,BNDataset learn.params,BN,BNDataset-method |
| learn the structure of a network. | learn.structure learn.structure,BN,BNDataset learn.structure,BN,BNDataset-method |
| compute the list of inferred marginals of a BN. | marginals marginals,InferenceEngine marginals,InferenceEngine-method |
| get name of an object. | name name,BN name,BN-method name,BNDataset name,BNDataset-method |
| set name of an object. | name<- name<-,BN-method name<-,BNDataset-method |
| get size of the variables of an object. | node.sizes node.sizes,BN node.sizes,BN-method node.sizes,BNDataset node.sizes,BNDataset-method |
| set the size of variables of an object. | node.sizes<- node.sizes<-,BN-method node.sizes<-,BNDataset-method |
| get number of bootstrap samples of a 'BNDataset'. | num.boots num.boots,BNDataset num.boots,BNDataset-method |
| set number of bootstrap samples of a 'BNDataset'. | num.boots<- num.boots<-,BNDataset-method |
| get number of items of a 'BNDataset'. | num.items num.items,BNDataset num.items,BNDataset-method |
| set number of items of a 'BNDataset'. | num.items<- num.items<-,BNDataset-method |
| get number of nodes of an object. | num.nodes num.nodes,BN num.nodes,BN-method num.nodes,InferenceEngine num.nodes,InferenceEngine-method |
| set number of nodes of an object. | num.nodes<- num.nodes<-,BN-method num.nodes<-,InferenceEngine-method |
| get number of time steps observed in a 'BN' or a 'BNDataset'. | num.time.steps num.time.steps,BN num.time.steps,BN-method num.time.steps,BNDataset num.time.steps,BNDataset-method |
| set number of time steps of a 'BN' or a 'BNDataset'. | num.time.steps<- num.time.steps<-,BN-method num.time.steps<-,BNDataset-method |
| get number of variables of a 'BNDataset'. | num.variables num.variables,BNDataset num.variables,BNDataset-method |
| set number of variables of a 'BNDataset'. | num.variables<- num.variables<-,BNDataset-method |
| get the list of observations of an 'InferenceEngine'. | observations observations,InferenceEngine observations,InferenceEngine-method |
| set the list of observations of an 'InferenceEngine'. | observations<- observations<-,InferenceEngine-method |
| plot a 'BN' as a picture. | plot plot,BN plot.BN plot.BN,BN |
| print a 'BN', 'BNDataset' or 'InferenceEngine' to 'stdout'. | print print,BN print,BNDataset print,InferenceEngine print.BN print.BN,BN print.BNDataset print.BNDataset,BNDataset print.InferenceEngine print.InferenceEngine,InferenceEngine |
| get the list of quantiles of an object. | quantiles quantiles,BN quantiles,BN-method quantiles,BNDataset quantiles,BNDataset-method |
| set the list of quantiles of an object. | quantiles<- quantiles<-,BN-method quantiles<-,BNDataset-method |
| get raw data of a BNDataset. | raw.data raw.data,BNDataset raw.data,BNDataset-method |
| add raw data. | raw.data<- raw.data<-,BNDataset-method |
| Read a network from a '.bif' file. | read.bif read.bif,character read.bif,character-method |
| Read a dataset from file. | read.dataset read.dataset,BNDataset,character,character read.dataset,BNDataset,character,character-method |
| Read a network from a '.dsc' file. | read.dsc read.dsc,character read.dsc,character-method |
| Read a network from a '.net' file. | read.net read.net,character read.net,character-method |
| sample a 'BNDataset' from a network of an inference engine. | sample.dataset sample.dataset,BN sample.dataset,BN-method sample.dataset,InferenceEngine sample.dataset,InferenceEngine-method |
| sample a row vector of values for a network. | sample.row sample.row,BN sample.row,BN-method |
| save a 'BN' picture as '.eps' file. | save.to.eps save.to.eps,BN,character save.to.eps,BN,character-method |
| Read the scoring function used to learn the structure of a network. | scoring.func scoring.func,BN scoring.func,BN-method |
| Set the scoring function used to learn the structure of a network. | scoring.func<- scoring.func<-,BN-method |
| compute the Structural Hamming Distance between two adjacency matrices. | shd |
| Show method for objects. | show show,AllTheClasses-method show,BN-method show,BNDataset-method show,InferenceEngine-method |
| Read the algorithm used to learn the structure of a network. | struct.algo struct.algo,BN struct.algo,BN-method |
| Set the algorithm used to learn the structure of a network. | struct.algo<- struct.algo<-,BN-method |
| check if an updated 'BN' is present in an 'InferenceEngine'. | test.updated.bn test.updated.bn,InferenceEngine test.updated.bn,InferenceEngine-method |
| tune the parameter k of the knn algorithm used in imputation. | tune.knn.impute |
| get the updated 'BN' object contained in an 'InferenceEngine'. | updated.bn updated.bn,InferenceEngine updated.bn,InferenceEngine-method |
| set the updated 'BN' object contained in an 'InferenceEngine'. | updated.bn<- updated.bn<-,InferenceEngine-method |
| get variables of an object. | variables variables,BN variables,BN-method variables,BNDataset variables,BNDataset-method |
| set variables of an object. | variables<- variables<-,BN-method variables<-,BNDataset-method |
| get the WPDAG of an object. | wpdag wpdag,BN wpdag,BN-method |
| Initialize a WPDAG from a DAG. | wpdag.from.dag wpdag.from.dag,BN wpdag.from.dag,BN-method |
| set WPDAG of the object. | wpdag<- wpdag<-,BN-method |
| Write a network saving it in an 'XGMML' file. | write_xgmml write_xgmml,BN write_xgmml,BN-method |
| Write a network saving it in a '.dsc' file. | write.dsc write.dsc,BN write.dsc,BN-method |