Ausgabe 1/2019
Special Issue on Advances on Model-Based Clustering and Classification
Inhalt (14 Artikel)
Special issue on “Advances on model-based clustering and classification”
Sylvia Frühwirth-Schnatter, Salvatore Ingrassia, Agustín Mayo-Iscar
Unifying data units and models in (co-)clustering
Christophe Biernacki, Alexandre Lourme
From here to infinity: sparse finite versus Dirichlet process mixtures in model-based clustering
Sylvia Frühwirth-Schnatter, Gertraud Malsiner-Walli
Clustering via finite nonparametric ICA mixture models
Xiaotian Zhu, David R. Hunter
Finite mixture of regression models for censored data based on scale mixtures of normal distributions
Camila Borelli Zeller, Celso Rômulo Barbosa Cabral, Víctor Hugo Lachos, Luis Benites
Finite mixture biclustering of discrete type multivariate data
Daniel Fernández, Richard Arnold, Shirley Pledger, Ivy Liu, Roy Costilla
Finite mixtures, projection pursuit and tensor rank: a triangulation
Nicola Loperfido
Clustering space-time series: FSTAR as a flexible STAR approach
Edoardo Otranto, Massimo Mucciardi
Robust clustering for functional data based on trimming and constraints
Diego Rivera-García, Luis A. García-Escudero, Agustín Mayo-Iscar, Joaquín Ortega
Assessing trimming methodologies for clustering linear regression data
Francesca Torti, Domenico Perrotta, Marco Riani, Andrea Cerioli
Variable selection in model-based clustering and discriminant analysis with a regularization approach
Gilles Celeux, Cathy Maugis-Rabusseau, Mohammed Sedki
Random effects clustering in multilevel modeling: choosing a proper partition
Claudio Conversano, Massimo Cannas, Francesco Mola, Emiliano Sironi
sARI: a soft agreement measure for class partitions incorporating assignment probabilities
Abby Flynt, Nema Dean, Rebecca Nugent
Studying crime trends in the USA over the years 2000–2012
Volodymyr Melnykov, Xuwen Zhu