The likelihood function of additive learning models: sufficient conditions for strict log-concavity and uniqueness of maximum

DOI10.1016/0022-2496(73)90005-9zbMath0249.92006OpenAlexW2061340803MaRDI QIDQ2556805

Donald D. Dorfman

Publication date: 1973

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

Full work available at URL: https://doi.org/10.1016/0022-2496(73)90005-9

Mathematics Subject Classification ID

Mathematical psychology (91E99)

Related Items (2)

Sufficient conditions for the uniqueness of parameter estimates from binary-response data ⋮ On a class of additive learning models: Error-correcting and probability matching

Cites Work

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• A generalization of a theorem of dimensional analysis
• Limit theorems for additive learning models
• A learning model for a continuum of sensory states
• Markov processes and learning models
• A Remark on the Roots of the Maximum Likelihood Equation
• The Lindeberg-Levy Theorem for Martingales
• Function minimization by conjugate gradients

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