Man pages for cbg-ethz/SubGroupSeparation
Inference in Bayesian Networks
| add.observations-set | add further evidence to an existing list of observations of... |
| approxInference | Importance Sampling (IS) in Bayesian Networks |
| Asia | Asia dataset |
| Asiamat | Asiamat |
| belief.propagation | perform belief propagation. |
| benchmarkMultipleNets | Benchmark Inference Methods |
| BN-class | BN class definition. |
| BNDataset-class | BNDataset class. |
| bn-method | get the 'BN' object contained in an 'InferenceEngine'. |
| bn-set | set the original 'BN' object contained in an... |
| boot | get selected element of bootstrap list. |
| boots | get list of bootstrap samples of a 'BNDataset'. |
| boots-set | set list of bootstrap samples of a 'BNDataset'. |
| bootstrap | Perform bootstrap. |
| build.junction.tree | build a JunctionTree. |
| complete | Subset a 'BNDataset' to get only complete cases. |
| convertBNBestieToSGS | Bayesian network Conversion Bestie to SGS format |
| convertCPTsBestieToSGS | CPTs Conversion Bestie to SGS format |
| cpts | get the list of conditional probability tables of a 'BN'. |
| cpts-set | set the list of conditional probability tables of a network. |
| dag | get adjacency matrix of a network. |
| dag-set | set adjacency matrix of an object. |
| dag.to.cpdag | convert a DAG to a CPDAG |
| data.file | get data file of a 'BNDataset'. |
| data.file-set | set data file of a 'BNDataset'. |
| discreteness | get status (discrete or continuous) of the variables of an... |
| discreteness-set | set status (discrete or continuous) of the variables of an... |
| edge.dir.wpdag | counts the edges in a WPDAG with their directionality |
| em | expectation-maximization algorithm. |
| exactInference | Exact inference via SupGroupSeparation |
| get.allAncestors | Get relevant DAG nodes (ancestors) |
| get.allSubGroups | Get All Conditionally Independent Subgroups (CIS) |
| get.most.probable.values | compute the most probable values to be observed. |
| get.subGroup | Get Conditionally Independent Subgroup (CIS) |
| has.boots | check whether a 'BNDataset' has bootstrap samples or not. |
| has.imputed.boots | check whether a 'BNDataset' has bootstrap samples from... |
| has.imputed.data | check if a BNDataset contains impited data. |
| has.raw.data | check if a BNDataset contains raw data. |
| header.file | get header file of a 'BNDataset'. |
| header.file-set | set header file of a 'BNDataset'. |
| imp.boots | get list of bootstrap samples from imputed data of a... |
| imp.boots-set | set list of bootstrap samples from imputed data of a... |
| impute | Impute a 'BNDataset' raw data with missing values. |
| imputed.data | get imputed data of a BNDataset. |
| imputed.data-set | add imputed data. |
| InferenceEngine-class | InferenceEngine class. |
| interventions | get the list of interventions of an 'InferenceEngine'. |
| interventions-set | set the list of interventions for an 'InferenceEngine'. |
| jpts | get the list of joint probability tables compiled by an... |
| jpts-set | set the list of joint probability tables compiled by an... |
| jt.cliques | get the list of cliques of the junction tree of an... |
| jt.cliques-set | set the list of cliques of the junction tree of an... |
| junction.tree | get the junction tree of an 'InferenceEngine'. |
| junction.tree-set | set the junction tree of an 'InferenceEngine'. |
| knn.impute | Perform imputation of a data frame using k-NN. |
| layering | return the layering of the nodes. |
| learn_bn | learn_bn |
| learn.dynamic.network | learn a dynamic network (structure and parameters) of a BN... |
| learn.network | learn a network (structure and parameters) of a BN from a... |
| learn.params | learn the parameters of a BN. |
| learn.structure | learn the structure of a network. |
| loopy_belief.propagation | perform LOOPY belief propagation. |
| makeAllPlots | Visualize benchmark results |
| marginals | compute the list of inferred marginals of a BN. |
| name | get name of an object. |
| name-set | set name of an object. |
| node.sizes | get size of the variables of an object. |
| node.sizes-set | set the size of variables of an object. |
| num.boots | get number of bootstrap samples of a 'BNDataset'. |
| num.boots-set | set number of bootstrap samples of a 'BNDataset'. |
| num.items | get number of items of a 'BNDataset'. |
| num.items-set | set number of items of a 'BNDataset'. |
| num.nodes | get number of nodes of an object. |
| num.nodes-set | set number of nodes of an object. |
| num.time.steps | get number of time steps observed in a 'BN' or a 'BNDataset'. |
| num.time.steps-set | set number of time steps of a 'BN' or a 'BNDataset'. |
| num.variables | get number of variables of a 'BNDataset'. |
| num.variables-set | set number of variables of a 'BNDataset'. |
| observations | get the list of observations of an 'InferenceEngine'. |
| observations-set | set the list of observations of an 'InferenceEngine'. |
| plot | plot a 'BN' as a picture. |
| plot_bn | plot_bn |
| plot_dag | plot_dag |
| print a 'BN', 'BNDataset' or 'InferenceEngine' to 'stdout'. | |
| quantiles | get the list of quantiles of an object. |
| quantiles-set | set the list of quantiles of an object. |
| randomBN | Create random Bayesian network |
| raw.data | get raw data of a BNDataset. |
| raw.data-set | add raw data. |
| read.bif | Read a network from a '.bif' file. |
| read.dataset | Read a dataset from file. |
| read.dsc | Read a network from a '.dsc' file. |
| read.net | Read a network from a '.net' file. |
| sample.dataset | sample a 'BNDataset' from a network of an inference engine. |
| sample.row | sample a row vector of values for a network. |
| sample.subGroupSampling | Sub Group Sampling (SGS) in Bayesian Networks |
| scoring.func | Read the scoring function used to learn the structure of a... |
| scoring.func-set | Set the scoring function used to learn the structure of a... |
| shd | compute the Structural Hamming Distance between two adjacency... |
| show | Show method for objects. |
| struct.algo | Read the algorithm used to learn the structure of a network. |
| struct.algo-set | Set the algorithm used to learn the structure of a network. |
| sub_belief.propagation | perform SUB belief propagation. |
| test.updated.bn | check if an updated 'BN' is present in an 'InferenceEngine'. |
| tune.knn.impute | tune the parameter k of the knn algorithm used in imputation. |
| updated.bn-method | get the updated 'BN' object contained in an... |
| updated.bn-set | set the updated 'BN' object contained in an... |
| variables | get variables of an object. |
| variables-set | set variables of an object. |
| wpdag | get the WPDAG of an object. |
| wpdag.from.dag | Initialize a WPDAG from a DAG. |
| wpdag-set | set WPDAG of the object. |
| write.dsc | Write a network saving it in a '.dsc' file. |
| write_xgmml | Write a network saving it in an 'XGMML' file. |
