Gaussian counter models for visual identification of briefly presented, mutually confusable single stimuli in pure accuracy tasks

DOI10.1016/j.jmp.2017.02.003zbMath1397.91537OpenAlexW2610021746WikidataQ55940827 ScholiaQ55940827MaRDI QIDQ1679039

Susanne Ditlevsen, Massimiliano Tamborrino, Søren Kyllingsbæk, Bo Markussen

Publication date: 8 November 2017

Published in: Journal of Mathematical Psychology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmp.2017.02.003

zbMATH Keywords

model selectionexit timesvisual categorizationmultivariate Wiener processmultivariate Ornstein-Uhlenbeck processvisual identification

Mathematics Subject Classification ID

Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Applications of Brownian motions and diffusion theory (population genetics, absorption problems, etc.) (60J70) Psychophysics and psychophysiology; perception (91E30) Applications of statistics to psychology (62P15)

Related Items (2)

First passage times of two-dimensional correlated processes: analytical results for the Wiener process and a numerical method for diffusion processes ⋮ Transient dynamics of Pearson diffusions facilitates estimation of rate parameters

Uses Software

• R

Cites Work

• Parameter inference from hitting times for perturbed Brownian motion
• A review of the methods for signal estimation in stochastic diffusion leaky integrate-and-fire neuronal models
• A note on modeling accumulation of information when the rate of accumulation changes over time
• Understanding the shape of the hazard rate: A process point of view. (With comments and a rejoinder).
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