cna-package | cna: A Package for Causal Modeling with Coincidence Analysis |

allCombs | Generate all logically possible value configurations of a given set of factors |

as.condTbl | Extract conditions and solutions from an object of class "cna" |

as.data.frame.condList | Methods for class "condList" |

asf | Extract conditions and solutions from an object of class "cna" |

cna | Perform Coincidence Analysis |

coherence | Calculate the coherence of complex solution formulas |

coherence.cti | Calculate the coherence of complex solution formulas |

coherence.default | Calculate the coherence of complex solution formulas |

condition | Uncover relevant properties of msc, asf, and csf in a data frame or 'configTable' |

condition.condTbl | Uncover relevant properties of msc, asf, and csf in a data frame or 'configTable' |

condition.default | Uncover relevant properties of msc, asf, and csf in a data frame or 'configTable' |

condList-methods | Methods for class "condList" |

condTbl | Extract conditions and solutions from an object of class "cna" |

configTable | Assemble cases with identical configurations in a configuration table |

csf | Extract conditions and solutions from an object of class "cna" |

ct2df | Transform a configuration table into a data frame |

cyclic | Detect cyclic substructures in complex solution formulas (csf) |

d.autonomy | Emergence and endurance of autonomy of biodiversity institutions in Costa Rica |

d.educate | Artificial data on education levels and left-party strength |

d.highdim | Artificial data with 50 factors and 1191 cases |

d.irrigate | Data on the impact of development interventions on water adequacy in Nepal |

d.jobsecurity | Job security regulations in western democracies |

d.minaret | Data on the voting outcome of the 2009 Swiss Minaret Initiative |

d.pacts | Data on the emergence of labor agreements in new democracies between 1994 and 2004 |

d.pban | Party ban provisions in sub-Saharan Africa |

d.performance | Data on combinations of industry, corporate, and business-unit effects |

d.volatile | Data on the volatility of grassroots associations in Norway between 1980 and 2000 |

d.women | Data on high percentage of women's representation in parliaments of western countries |

full.ct | Generate the logically possible value configurations of a given set of factors |

full.ct.configTable | Generate the logically possible value configurations of a given set of factors |

full.ct.cti | Generate the logically possible value configurations of a given set of factors |

full.ct.default | Generate the logically possible value configurations of a given set of factors |

group.by.outcome | Methods for class "condList" |

identical.model | Identify correctness-preserving submodel relations |

is.inus | Check whether expressions in the syntax of CNA solutions have INUS form |

is.submodel | Identify correctness-preserving submodel relations |

makeFuzzy | Fuzzifying crisp-set data |

minimalize | Eliminate logical redundancies from Boolean expressions |

minimalizeCsf | Eliminate structural redundancies from csf |

minimalizeCsf.cna | Eliminate structural redundancies from csf |

minimalizeCsf.default | Eliminate structural redundancies from csf |

msc | Extract conditions and solutions from an object of class "cna" |

print.cna | Perform Coincidence Analysis |

print.cond | Uncover relevant properties of msc, asf, and csf in a data frame or 'configTable' |

print.condList | Uncover relevant properties of msc, asf, and csf in a data frame or 'configTable' |

print.condTbl | Extract conditions and solutions from an object of class "cna" |

print.configTable | Assemble cases with identical configurations in a configuration table |

randomAsf | Generate random solution formulas |

randomConds | Generate random solution formulas |

randomCsf | Generate random solution formulas |

redundant | Identify structurally redundant asf in a csf |

rreduce | Eliminate redundancies from a disjunctive normal form (DNF) |

selectCases | Select the cases/configurations compatible with a data generating causal structure |

selectCases1 | Select the cases/configurations compatible with a data generating causal structure |

some | Randomly select configurations from a data frame or 'configTable' |

some.configTable | Randomly select configurations from a data frame or 'configTable' |

some.data.frame | Randomly select configurations from a data frame or 'configTable' |

summary.condList | Methods for class "condList" |