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20112022
most citedLearning Attribute Patterns in High-Dimensional Structured Latent Attribute Models

15 citations · 21 across the 6 of their papers we have counts for

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10 papers

math.ST20201 cited

On the Phase Transition of Wilk's Phenomenon

Yinqiu He, Bo Meng, Zhenghao Zeng +1

Wilk's theorem, which offers universal chi-squared approximations for likelihood ratio tests, is widely used in many scientific hypothesis testing problems. For modern datasets wit…

stat.ME2020

Sequential Gibbs Sampling Algorithm for Cognitive Diagnosis Models with Many Attributes

Juntao Wang, Ningzhong Shi, Xue Zhang +1

Cognitive diagnosis models (CDMs) are useful statistical tools to provide rich information relevant for intervention and learning. As a popular approach to estimate and make infere…

stat.ME201915 cited

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…

math.ST2018

Likelihood Ratio Test in Multivariate Linear Regression: from Low to High Dimension

Yinqiu He, Tiefeng Jiang, Jiyang Wen +1

Multivariate linear regressions are widely used statistical tools in many applications to model the associations between multiple related responses and a set of predictors. To infe…

math.ST2018

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…

math.ST2018

Asymptotically Independent U-Statistics in High-Dimensional Testing

Yinqiu He, Gongjun Xu, Chong Wu +1

Many high-dimensional hypothesis tests aim to globally examine marginal or low-dimensional features of a high-dimensional joint distribution, such as testing of mean vectors, covar…