Iteratively do sufficiency tests on k features out of the given features

This function iteratively generates all combinations of k features from the given feature vector (n choose k), and perform a sufficiency test for each combination of the k features.

Usage

iterQCA(
  features,
  k,
  dataCali,
  outcome,
  incl.cut = 0.8,
  pri.cut = 0.51,
  n.cut = 10,
  sort.by = c("OUT", "incl"),
  complete = T
)

Arguments

features: string vector, a vector of features to choose from
k: number, number of features to choose for each sufficiency test
dataCali: dataframe, calibrated data
outcome: string, name of the outcome variable
incl.cut: inclusion cut-off(s); see `?QCA::truthTable` for details
pri.cut: minimal score for the PRI; see `?QCA::truthTable` for details
n.cut: minimum number of cases for a remainder row; see `?QCA::truthTable` for details
sort.by: Sort the truth table according to various columns
complete: Logical, whether to print complete truth table

Value

a summary table of solutions to all combinations of k out of n feautres

Examples

if (FALSE) { # \dontrun{
fDf <- getFeatureImp(xgb, voteData, "vote")
fVec <- head(fDf$feature, 10)
iterQCA(features = fVec, k=4, dataCali = voteDataCalibrated, outcome = "vote")
} # }