Searches configurational data for causes that are each an
insufficient but non-redundant part of an unnecessary but sufficient
(INUS) condition for their effect, so that cause-effect relations are
marked by conjunctivity and disjunctivity. The method, Combinational
Regularity Analysis (CORA), borrows its Boolean minimisation algorithms
from switching circuit analysis. Truth tables are minimised either with the
classical Quine-McCluskey algorithm over positive and don't care terms or
with McCluskey's modified algorithm over positive and negative terms, and
the resulting prime implicant charts are solved with Petrick's method.
Multi-value conditions and structures with simple as well as complex
effects are supported, together with a configurational data-mining search
and two-level logic diagrams. The package is an R port of the 'Python'
packages 'CORA' and 'LOGIGRAM' described in Sebechlebská, Mkrtchyan
and Thiem (2023)