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Directed Clustering of Multivariate Data Based on Linear or Quadratic Latent Variable Models (2024)
Journal Article
Zhang, Y., & Einbeck, J. (2024). Directed Clustering of Multivariate Data Based on Linear or Quadratic Latent Variable Models. Algorithms, 17(8), Article 358. https://doi.org/10.3390/a17080358

We consider situations in which the clustering of some multivariate data is desired, which establishes an ordering of the clusters with respect to an underlying latent variable. As our motivating example for a situation where such a technique is desi... Read More about Directed Clustering of Multivariate Data Based on Linear or Quadratic Latent Variable Models.

A Versatile Model for Clustered and Highly Correlated Multivariate Data (2024)
Journal Article
Zhang, Y., & Einbeck, J. (2024). A Versatile Model for Clustered and Highly Correlated Multivariate Data. Journal of statistical theory and practice, 18(1), Article 5. https://doi.org/10.1007/s42519-023-00357-0

For the analysis of multivariate data with an approximately one-dimensional latent structure, it is suggested to model this latent variable by a random effect, allowing for the use of mixed model methodology for dimension reduction purposes. We imple... Read More about A Versatile Model for Clustered and Highly Correlated Multivariate Data.