Dirichlet Process Mixture Models for Modeling and Generating Synthetic Versions of Nested Categorical Data

Research article (Bayesian Analysis, 2017) · cited 52× · AI/ML
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Dirichlet Process Mixture Models for Modeling and Generating Synthetic Versions of Nested Categorical Data

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Dirichlet Process Mixture Models for Modeling and Generating Synthetic Versions of Nested Categorical Data is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Dirichlet Process Mixture Models for Modeling and Generating Synthetic Versions of Nested Categorical Data. Retrieved May 24, 2026, from https://4ort.xyz/entity/dirichlet-process-mixture-models-for-modeling-and-generating-synthetic-versions-of-nested-categorical-data
MLA “Dirichlet Process Mixture Models for Modeling and Generating Synthetic Versions of Nested Categorical Data.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/dirichlet-process-mixture-models-for-modeling-and-generating-synthetic-versions-of-nested-categorical-data.
BibTeX @misc{4ortxyz_dirichlet-process-mixture-models-for-modeling-and-generating-synthetic-versions-of-nested-categorical-data_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Dirichlet Process Mixture Models for Modeling and Generating Synthetic Versions of Nested Categorical Data}}, year = {2026}, url = {https://4ort.xyz/entity/dirichlet-process-mixture-models-for-modeling-and-generating-synthetic-versions-of-nested-categorical-data}, note = {Accessed: 2026-05-24}}
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