Reformulating Markovian processes for learning and memory from a hazard function framework
From MaRDI portal
Publication:396226
DOI10.1016/j.jmp.2013.09.004zbMath1309.91119OpenAlexW2057672422MaRDI QIDQ396226
Lara N. Sloboda, Richard A. Chechile
Publication date: 8 August 2014
Published in: Journal of Mathematical Psychology (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jmp.2013.09.004
Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Memory and learning in psychology (91E40) Estimation in survival analysis and censored data (62N02)
Related Items
A Bayesian analysis for the Wilcoxon signed-rank statistic ⋮ A Bayesian analysis for the Mann-Whitney statistic ⋮ Extended decision field theory with social-learning for long-term decision-making processes in social networks
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Obtaining separate measures for implicit and explicit memory
- The form of the forgetting curve and the fate of memories
- Properties of reverse hazard functions
- Reconsidering the two-second decay hypothesis in verbal working memory
- Representation of measures by balayage from a regular recurrent point
- A Bayesian procedure for separately estimating storage and retrieval components of forgetting
- Serial and within-stage independent parallel model equivalence on the minimum completion time
- Cramér theorem on symmetric spaces of noncompact type
- Mathematical tools for hazard function analysis.
- New multinomial models for the Chechile-Meyer task
- Hitting and return times in ergodic dynamical systems
- Application of a model to paired-associate learning
- A statistical description of verbal learning
