Distribution inequalities for parallel models with unlimited capacity
type: Item
instance of: scholarly article
title: Distribution inequalities for parallel models with unlimited capacity
zbMATH Open document ID: 0840.92031
author: Hans Colonius
author: Dirk Vorberg
published in: Journal of Mathematical Psychology
publication date: 1996-06-24T00:00:00Z
review text: 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.
Mathematics Subject Classification ID: 91E45
Mathematics Subject Classification ID: 62P15
Mathematics Subject Classification ID: 60E15
zbMATH DE Number: 554102
zbMATH Keywords: reaction time distribution
zbMATH Keywords: n-channel parallel models
zbMATH Keywords: unlimited capacity assumption
zbMATH Keywords: stochastic dependence properties
zbMATH Keywords: finite mixture distributions
zbMATH Keywords: limited capacity
zbMATH Keywords: reaction time measurements
zbMATH Keywords: models of parallel processes
MaRDI profile type: Publication
full work available at URL: jmps.1994.1002
OpenAlex ID: W2069951284
DOI: 10.1006/JMPS.1994.1002
description: scientific article; zbMATH DE number 554102