The nested logit model has been used extensively to model multi-dimensional choice situations. A drawback of the nested logit model is that it does not allow choice alternatives to share common unobserved attributes along all the dimensions characterizing the multi-dimensional choice context. This paper formulates a mixed multinomial logit structure that accommodates unobserved correlation acro...

The authors analyzed source memory performance with an unequal-variance signal detection theory model and compared the findings with extant threshold (multinomial and dual-process) models. In 3 experiments, receiver operating characteristic (ROC) analyses of source discrimination revealed curvilinear functions, supporting the relative superiority of a continuous signal detection model when comp...

Methods Existing multivariate algorithms only model disease-relevant data streams (e.g., anti-fever medication sales or patient visits with constitutional syndrome for detection of flu outbreak). On the contrary, we also incorporate a non-disease-relevant data stream as a control factor. We assume that the counts from all data streams follow a Multinomial distribution. Given this distribution, ...

To address the mechanism underlying the development of episodic memory, the current study used a modified list learning paradigm for children (i.e. ABCD, ABAC, ABABr) and compared the performance of 4 year-olds, 7 year-olds, and adults. The results show that only the ABABr condition, which involves a 3-way binding structure, differed across age. Additionally, a proposed computational model (mul...

In this work, we develop and evaluate a wide range of feature spaces for deriving Levinstyle verb classifications (Levin, 1993). We perform the classification experiments using Bayesian Multinomial Regression (an efficient log-linear modeling framework which we found to outperform SVMs for this task) with the proposed feature spaces. Our experiments suggest that subcategorization frames are not...