publications
upcoming articles
–> Rayleigh Lei and Abel Rodriguez. 2024. Modeling Ordinal Survey Data with Unfolding Models. Under preparation.
–> Rayleigh Lei and Abel Rodriguez. 2024. Logistic Unfolding Models for Binary Preference Data. Revised and resubmitted to Statistics and Computing. https://arxiv.org/abs/2407.06395.
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Sunrit Chakraborty*, Rayleigh Lei*, and (Xuan)Long Nguyen. 2024. Learning Topic Hierarchies by Tree-Directed Latent Variable Models. Under review in Bernoulli. https://arxiv.org/abs/2408.14327.
* co-first author
–> Rayleigh Lei and (Xuan)Long Nguyen. 2024. Modeling Random Direction of Changes in Simplex-valued Data. Under review in Communications in Statistics - Theory and Methods. https://arxiv.org/abs/2310.19985.
journal articles
–> Rayleigh Lei and Abel Rodriguez. 2024. A Novel Class of Unfolding Models for Binary Preference Data. Political Analysis. https://doi.org/10.1017/pan.2024.11.
–> Rayleigh Lei and Abel Rodriguez. August 2024. Dynamic Factor Models for Binary Data in Circular Spaces: An Application to the U.S. Supreme Court. Journal of the Royal Statistical Society Series C: Applied Statistics, Volume 73, Issue 4, Pages 1042 - 1064. https://doi.org/10.1093/jrsssc/qlae025.
–> Sunrit Chakraborty, Aritra Guha, Rayleigh Lei, XuanLong Nguyen. Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence, PMLR 216:282-292, 2023. https://proceedings.mlr.press/v216/chakraborty23a.html.
–> Aritra Guha, Rayleigh Lei, Jiacheng Zhu, XuanLong Nguyen, and Ding Zhao. 2022. Robust unsupervised learning of temporal dynamic vehicle-to-vehicle interactions, Transportation Research Part C: Emerging Technologies, Volume 142, 103768, https://doi.org/10.1016/j.trc.2022.103768.
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Rayleigh Lei, Andrew Gelman, and Yair Ghitza. 2017. The 2008 Election: A Preregistered Replication Analysis. Statistics and Public Policy, 4 (1), 1-8. https://doi.org/10.1080/2330443X.2016.1277966.
dissertation
–> Modeling Simplex-value Data and Latent Structures. 2022. https://deepblue.lib.umich.edu/handle/2027.42/174205.