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Hierarchical Normalized Completely Random Measures to Cluster Grouped Data

  • Published:2019-05-17 Issue:529 Volume:115 Page:318-333
  • ISSN:0162-1459
  • Container-title:Journal of the American Statistical Association
  • language:en
  • Short-container-title:Journal of the American Statistical Association

Author:

Argiento Raffaele1ORCID,Cremaschi Andrea23ORCID,Vannucci Marina4ORCID

Affiliation:

1. ESOMAS Department, University of Torino and Collegio Carlo Alberto, Torino, Italy;

2. Department of Cancer Immunology, Institute of Cancer Research, Oslo University Hospital, Oslo, Norway;

3. Oslo Centre for Biostatistics and Epidemiology, University of Oslo, Oslo, Norway;

4. Department of Statistics, Rice University, Houston, TX

Funder

Marina Vannucci partially supported by

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

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1. Blocked Gibbs sampler for hierarchical Dirichlet processes;Journal of Computational and Graphical Statistics;2024-08-05

2. Graph-Aligned Random Partition Model (GARP);Journal of the American Statistical Association;2024-05-30

3. Shared Differential Clustering across Single-cell RNA Sequencing Datasets with the Hierarchical Dirichlet Process;Econometrics and Statistics;2024-02

4. Immune Profiling among Colorectal Cancer Subtypes using Dependent Mixture Models;2023-07-26

5. Normalised latent measure factor models;Journal of the Royal Statistical Society Series B: Statistical Methodology;2023-06-23
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