Tadamasa Sawada,Qasim Zaidi
Tadamasa Sawada
A 3D shape of an object is N-fold rotational-symmetric if the shape is invariant for 360/N degree rotations about an axis. Human observers are sensitive to the 2D rotational-symmetry of a retinal image, but they are less sensitive than they...
Yuelin Li,Elizabeth Schofield,Mithat Gönen
Yuelin Li
Bayesian nonparametric (BNP) models are becoming increasingly important in psychology, both as theoretical models of cognition and as analytic tools. However, existing tutorials tend to be at a level of abstraction largely impenetrable by n...
Multinomial Models with Linear Inequality Constraints: Overview and Improvements of Computational Methods for Bayesian Inference [0.03%]
带线性不等式约束的多项式模型：贝叶斯推理的计算方法综述及改进
Daniel W Heck,Clintin P Davis-Stober
Daniel W Heck
Many psychological theories can be operationalized as linear inequality constraints on the parameters of multinomial distributions (e.g., discrete choice analysis). These constraints can be described in two equivalent ways: Either as the so...
Clintin P Davis-Stober,Jean-Paul Doignon,Samuel Fiorini et al.
Clintin P Davis-Stober et al.
Mathematical psychology has a long tradition of modeling probabilistic choice via distribution-free random utility models and associated random preference models. For such models, the predicted choice probabilities often form a bounded and ...
Thermodynamic Integration and Steppingstone Sampling Methods for Estimating Bayes Factors: A Tutorial [0.03%]
贝叶斯因子的热动力积分支法与过渡采样法教程
Jeffrey Annis,Nathan J Evans,Brent J Miller et al.
Jeffrey Annis et al.
One of the more principled methods of performing model selection is via Bayes factors. However, calculating Bayes factors requires marginal likelihoods, which are integrals over the entire parameter space, making estimation of Bayes factors...
Rejection odds and rejection ratios: A proposal for statistical practice in testing hypotheses [0.03%]
拒绝几率与拒绝比值：关于检验假设的统计方法实践提案
M J Bayarri,Daniel J Benjamin,James O Berger et al.
M J Bayarri et al.
Much of science is (rightly or wrongly) driven by hypothesis testing. Even in situations where the hypothesis testing paradigm is correct, the common practice of basing inferences solely on p-values has been under intense criticism for over...
Thomas J Palmeri,Bradley C Love,Brandon M Turner
Thomas J Palmeri
This special issue explores the growing intersection between mathematical psychology and cognitive neuroscience. Mathematical psychology, and cognitive modeling more generally, has a rich history of formalizing and testing hypotheses about ...
Integer Programs for One- and Two-Mode Blockmodeling Based on Prespecified Image Matrices for Structural and Regular Equivalence [0.03%]
基于结构等价和规则等价预设图像矩阵的一模和二模模块化整数规划模型
Michael J Brusco,Douglas Steinley
Michael J Brusco
Establishing blockmodels for one- and two-mode binary network matrices has typically been accomplished using multiple restarts of heuristic algorithms that minimize functions of inconsistency with ideal block structure. Although these algor...
Quentin F Gronau,Alexandra Sarafoglou,Dora Matzke et al.
Quentin F Gronau et al.
The marginal likelihood plays an important role in many areas of Bayesian statistics such as parameter estimation, model comparison, and model averaging. In most applications, however, the marginal likelihood is not analytically tractable a...
Model-based functional neuroimaging using dynamic neural fields: An integrative cognitive neuroscience approach [0.03%]
基于动态神经场的功能性神经影像学：一种整合认知神经科学的方法
Sobanawartiny Wijeakumar,Joseph P Ambrose,John P Spencer et al.
Sobanawartiny Wijeakumar et al.
A fundamental challenge in cognitive neuroscience is to develop theoretical frameworks that effectively span the gap between brain and behavior, between neuroscience and psychology. Here, we attempt to bridge this divide by formalizing an i...