big10

The data was randomly generated using set.seed(10)

datasets

Performs the Quine-McCluskey algorithm for Qualitative
        Comparative Analysis, for both crisp versions: bvQCA
        (binary-value QCA) and for mvQCA (multi-value QCA). In the
        classical approach it currently handles about 15 conditions and
        one outcome for binary data only, but since version 0.4-5 the
        package has an enhanced, faster function that obtains the same
        exact solutions with a substantially lower memory consumption,
        it handles even more causal conditions; the enhanced function
        eqmcc() can also be used for mvQCA. The next versions of this
        algorithm will be oriented towards fuzzy-set functions. Also,
        in the near future the current functions will deal with missing
        values in the data

big10: Random data with 10 conditions and 1 outcome

Description

Usage

Arguments