Causal Modeling with Coincidence Analysis


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Documentation for package ‘cna’ version 2.2.0

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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"
asf Extract conditions and solutions from an object of class "cna"
cna Perform Coincidence Analysis
coherence Calculate the coherence of complex solution formulas
condition Uncover relevant properties of msc, asf, and csf in a data frame or 'truthTab'
condition.condTbl Uncover relevant properties of msc, asf, and csf in a data frame or 'truthTab'
condition.default Uncover relevant properties of msc, asf, and csf in a data frame or 'truthTab'
condTbl Extract conditions and solutions from an object of class "cna"
cscna Perform Coincidence Analysis
cscond Uncover relevant properties of msc, asf, and csf in a data frame or 'truthTab'
csf Extract conditions and solutions from an object of class "cna"
cstt Assemble cases with identical configurations in a truth table
cyclic Detect cyclic substructures in complex solution formulas (csf)
d.autonomy Emergence and endurance of autonomy of biodiversity institutions in Costa Rica
d.educate Artifical data on education levels and left-party strength
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 represention in parliaments of western countries
fscna Perform Coincidence Analysis
fscond Uncover relevant properties of msc, asf, and csf in a data frame or 'truthTab'
fstt Assemble cases with identical configurations in a truth table
full.tt Generate all logically possible value configurations of a given set of factors
full.tt.default Generate all logically possible value configurations of a given set of factors
full.tt.truthTab Generate all logically possible value configurations of a given set of factors
full.tt.tti Generate all logically possible value configurations of a given set of factors
group.by.outcome Uncover relevant properties of msc, asf, and csf in a data frame or 'truthTab'
identical.model Identify correctness-preserving submodel relations
is.inus Test disjunctive normal forms for logical redundancies
is.submodel Identify correctness-preserving submodel relations
makeFuzzy Generate fuzzy-set data by simulating noise
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"
mvcna Perform Coincidence Analysis
mvcond Uncover relevant properties of msc, asf, and csf in a data frame or 'truthTab'
mvtt Assemble cases with identical configurations in a truth table
print.cna Perform Coincidence Analysis
print.cond Uncover relevant properties of msc, asf, and csf in a data frame or 'truthTab'
print.condList Uncover relevant properties of msc, asf, and csf in a data frame or 'truthTab'
print.condTbl Extract conditions and solutions from an object of class "cna"
print.minimalizeCsf Eliminate structural redundancies from csf
print.truthTab Assemble cases with identical configurations in a truth table
randomAsf Generate random solution formulas
randomConds Generate random solution formulas
randomCsf Generate random solution formulas
redundant Identify structurally redundant asf in a csf
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 'truthTab'
some.data.frame Randomly select configurations from a data frame or 'truthTab'
some.truthTab Randomly select configurations from a data frame or 'truthTab'
summary.condList Uncover relevant properties of msc, asf, and csf in a data frame or 'truthTab'
truthTab Assemble cases with identical configurations in a truth table
tt2df Transform a truth table into a data frame