89 citations · 178 across the 12 of their papers we have counts for
12 papers
A Spectral Method for Identifiable Grade of Membership Analysis with Binary Responses
Ling Chen, Yuqi Gu
Grade of Membership (GoM) models are popular individual-level mixture models for multivariate categorical data. GoM allows each subject to have mixed memberships in multiple extrem…
Latent Conjunctive Bayesian Network: Unify Attribute Hierarchy and Bayesian Network for Cognitive Diagnosis
Seunghyun Lee, Yuqi Gu
Cognitive diagnostic assessment aims to measure specific knowledge structures in students. To model data arising from such assessments, cognitive diagnostic models with discrete la…
Blessing of Dependence: Identifiability and Geometry of Discrete Models with Multiple Binary Latent Variables
Yuqi Gu
Identifiability of discrete statistical models with latent variables is known to be challenging to study, yet crucial to a model's interpretability and reliability. This work prese…
Dimension-Grouped Mixed Membership Models for Multivariate Categorical Data
Yuqi Gu, Elena A. Erosheva, Gongjun Xu +1
Mixed Membership Models (MMMs) are a popular family of latent structure models for complex multivariate data. Instead of forcing each subject to belong to a single cluster, MMMs in…
A Tensor-EM Method for Large-Scale Latent Class Analysis with Binary Responses
Zhenghao Zeng, Yuqi Gu, Gongjun Xu
Latent class models are powerful statistical modeling tools widely used in psychological, behavioral, and social sciences. In the modern era of data science, researchers often have…
Bayesian Pyramids: Identifiable Multilayer Discrete Latent Structure Models for Discrete Data
Yuqi Gu, David B. Dunson
High dimensional categorical data are routinely collected in biomedical and social sciences. It is of great importance to build interpretable parsimonious models that perform dimen…
A Joint MLE Approach to Large-Scale Structured Latent Attribute Analysis
Yuqi Gu, Gongjun Xu
Structured Latent Attribute Models (SLAMs) are a family of discrete latent variable models widely used in education, psychology, and epidemiology to model multivariate categorical…
Identifiability of Hierarchical Latent Attribute Models
Yuqi Gu, Gongjun Xu
Hierarchical Latent Attribute Models (HLAMs) are a family of discrete latent variable models that are attracting increasing attention in educational, psychological, and behavioral…
Learning Attribute Patterns in High-Dimensional Structured Latent Attribute Models
Yuqi Gu, Gongjun Xu
Structured latent attribute models (SLAMs) are a special family of discrete latent variable models widely used in social and biological sciences. This paper considers the problem o…
Sufficient and Necessary Conditions for the Identifiability of the -matrix
Yuqi Gu, Gongjun Xu
Restricted latent class models (RLCMs) have recently gained prominence in educational assessment, psychiatric evaluation, and medical diagnosis. Different from conventional latent…
Partial Identifiability of Restricted Latent Class Models
Yuqi Gu, Gongjun Xu
Latent class models have wide applications in social and biological sciences. In many applications, pre-specified restrictions are imposed on the parameter space of latent class mo…
The Sufficient and Necessary Condition for the Identifiability and Estimability of the DINA Model
Yuqi Gu, Gongjun Xu
Cognitive Diagnosis Models (CDMs) are useful statistical tools in cognitive diagnosis assessment. However, as many other latent variable models, the CDMs often suffer from the non-…