Distribution inequalities for parallel models with unlimited capacity
It is generally assumed that the processing of information in a reaction time task can be decomposed into several subprocesses. A number of authors have shown that, in general, it is not possible to infer from reaction time measurements whether these subprocesses operate in parallel or serially. However, if additional assumptions are introduced constraining the class of possible models, testable conditions on their reaction time distributions can eventually be derived. \textit{J. T. Townsend} and \textit{F. G. Ashby} [The stochastic modeling of elementary psychological processes. (1983; Zbl 0595.92015); Chap. 8]\ derived a host of results on both parallel and serial self-terminating and exhaustive systems under various conditions of independence and capacity. The aim of this paper is to extend this approach to models of parallel processes only constrained by an assumption of ``limited capacity''. Systems of reaction time distribution function inequalities are derived that must hold for any model within that class.
scientific article; zbMATH DE number 554102