Characterizing random variables in the context of signal detection theory

DOI10.1016/0165-4896(92)90015-WzbMath0745.60039OpenAlexW1967839092MaRDI QIDQ1185292

Geoffrey J. Iverson, Ching-Fan Sheu

Publication date: 28 June 1992

Published in: Mathematical Social Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0165-4896(92)90015-w

zbMATH Keywords

characterizing detection modelsnotion of bisymmetrypartially stable random variablesstandard normal model

Mathematics Subject Classification ID

Infinitely divisible distributions; stable distributions (60E07) Signal detection and filtering (aspects of stochastic processes) (60G35)

Related Items (4)

A selective review of recent characterizations of stochastic choice models using distribution and functional equation techniques ⋮ Nonparametric relationships between single-interval and two-interval forced-choice tasks in the theory of signal detectability ⋮ Triadic judgment models and Weber's law ⋮ The normal distribution derived from qualitative conditions.

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• Transformations that render curves parallel
• Conditions for the representation of absolute judgment and pair comparison isosensitivity curves by cumulative distributions
• Transforming curves into curves with the same shape
• Non-Negative Measurable Solutions of Difference Equations
• On a Problem Connected with Beta and Gamma Distributions

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