Identification model based on the maximum information entropy principle

DOI10.1006/jmps.1999.1286zbMath1168.91514OpenAlexW2066350730WikidataQ52088533 ScholiaQ52088533MaRDI QIDQ1598967

Hisao Miyano

Publication date: 4 June 2002

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

Full work available at URL: https://doi.org/10.1006/jmps.1999.1286

Mathematics Subject Classification ID

Measurement and performance in psychology (91E45)

Related Items (1)

Probabilistic choice (models) as a result of balancing multiple goals

Cites Work

• Stimulus and response generalization: A stochastic model relating generalization to distance in psychological space
• A multidimensional stochastic theory of similarity
• Comparing the biased choice model and multidimensional decision bound models of identification
• Alternative biased choice models
• Maximum entropy interpretation of decision bound and context models of categorization
• A response time theory of separability and integrality in speeded classification
• Maximum entropy inference and stimulus generalization
• Axiomatic thermodynamics and extensive measurement
• Toward a Universal Law of Generalization for Psychological Science
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Axiomatic derivation of the principle of maximum entropy and the principle of minimum cross-entropy
• Vector quantization by deterministic annealing
• Self-Organization and Information

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