Statistics, Department of

 

The R Journal

Date of this Version

12-2018

Document Type

Article

Citation

The

Comments

Copyright 2018, The R Foundation. Open access material. License: CC BY 4.0 International

Abstract

A lot of effort has been spent over the past few decades in the QCA methodology field, to develop efficient Boolean minimization algorithms to derive an exact,and more importantly complete list of minimal prime implicants that explain the initial, observed positive configurations.

As the complexity grows exponentially with every new condition, the required computer memory goes past the current computer resources and the polynomial time required to solve this problem quickly grows towards infinity.

This paper introduces a new alternative to the existing non-polynomial attempts. It completely solves the memory problem, and preliminary tests show it is exponentially hundreds of time faster than eQMC, the current “best” algorithm for QCAinR, and probes into a territory where it competes and even out performs engineering algorithms such as Espresso, for exact minimizations.

While speed is not much of an issue now (eQMC is fast enough for simple data), it might prove to be essential when further developing towards all possible temporal orders, or searching for configurations in panel data over time,combined with/or automatic detection of difficult counterfactuals etc.

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