Assessing model mimicry using the parametric bootstrap
We present a general sampling procedure to quantify model mimicry, defined as the ability
of a model to account for data generated by a competing model. This sampling procedure …
of a model to account for data generated by a competing model. This sampling procedure …
Learning models of quantum systems from experiments
As Hamiltonian models underpin the study and analysis of physical and chemical
processes, it is crucial that they are faithful to the system they represent. However …
processes, it is crucial that they are faithful to the system they represent. However …
Optimal experimental design for model discrimination.
Abstract Models of a psychological process can be difficult to discriminate experimentally
because it is not easy to determine the values of the critical design variables (eg …
because it is not easy to determine the values of the critical design variables (eg …
Heterogeneity of strategy use in the Iowa gambling task: A comparison of win-stay/lose-shift and reinforcement learning models
The Iowa gambling task (IGT) has been used in numerous studies, often to examine
decision-making performance in different clinical populations. Reinforcement learning (RL) …
decision-making performance in different clinical populations. Reinforcement learning (RL) …
Bayes factors: Prior sensitivity and model generalizability
Model selection is a central issue in mathematical psychology. One useful criterion for model
selection is generalizability; that is, the chosen model should yield the best predictions for …
selection is generalizability; that is, the chosen model should yield the best predictions for …
Comparing prototype-based and exemplar-based accounts of category learning and attentional allocation.
JP Minda, JD Smith - Journal of Experimental Psychology: Learning …, 2002 - psycnet.apa.org
Exemplar theory was motivated by research that often used DL Medin and MM Schaffer's
(1978) 5/4 stimulus set. The exemplar model has seemed to fit categorization data from this …
(1978) 5/4 stimulus set. The exemplar model has seemed to fit categorization data from this …
High granular and short term time series forecasting of air pollutant - a comparative review
Forecasting time series has acquired immense research importance and has vast
applications in the area of air pollution monitoring. This work attempts to investigate the …
applications in the area of air pollution monitoring. This work attempts to investigate the …
How to quantify support for and against the null hypothesis: A flexible WinBUGS implementation of a default Bayesian t test
R Wetzels, JGW Raaijmakers, E Jakab… - Psychonomic bulletin & …, 2009 - Springer
We propose a sampling-based Bayesian t test that allows researchers to quantify the
statistical evidence in favor of the null hypothesis. This Savage—Dickey (SD) t test is …
statistical evidence in favor of the null hypothesis. This Savage—Dickey (SD) t test is …
Recognition ROCs are curvilinear—or are they? On premature arguments against the two-high-threshold model of recognition.
A Bröder, J Schütz - Journal of Experimental Psychology: Learning …, 2009 - psycnet.apa.org
Abstract [Correction Notice: An erratum for this article was reported in Vol 37 (5) of Journal of
Experimental Psychology: Learning, Memory, and Cognition (see record 2011-14286-001) …
Experimental Psychology: Learning, Memory, and Cognition (see record 2011-14286-001) …
Modeling individual differences using Dirichlet processes
We introduce a Bayesian framework for modeling individual differences, in which subjects
are assumed to belong to one of a potentially infinite number of groups. In this model, the …
are assumed to belong to one of a potentially infinite number of groups. In this model, the …