Statistical methods for absorbing Markov-chain models for learning: Estimation and identification

DOI10.1007/BF02291573zbMath0325.62056MaRDI QIDQ1225425

Peter G. Polson, David Huizinga

Publication date: 1974

Published in: Psychometrika (Search for Journal in Brave)

Mathematics Subject Classification ID

Measures of association (correlation, canonical correlation, etc.) (62H20) Markov processes: estimation; hidden Markov models (62M05) Mathematical psychology (91E99) Applications of statistics to psychology (62P15)

Related Items (3)

Population states and eigenstructures: A simplifying view of Markov learning models ⋮ How many parameters can a model have and still be testable? ⋮ An identifiable model of two-stage learning

Cites Work

• Presolution performance functions for Markov models
• Derivation of learning process statistics for a general Markov model
• Markovian processes with identifiable states: General considerations and application to all-or-none learning
• Paired-associate learning with short-term retention: Mathematical analysis and data regarding identification of parameters
• Derivations of learning statistics from absorbing Markov chains
• Statistical methods for a general theory of all-or-none learning
• Matrix analysis of identifiability of some finite Markov models
• `` Direct Search Solution of Numerical and Statistical Problems
• A Survey of Numerical Methods for Unconstrained Optimization
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