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Advances in Data Analysis and Classification, Volume 13
Volume 13, Number 1, March 2019
- Sylvia Frühwirth-Schnatter, Salvatore Ingrassia

, Agustín Mayo-Íscar
:
Special issue on "Advances on model-based clustering and classification" - Preface by the Guest Editors. 1-5 - Christophe Biernacki

, Alexandre Lourme:
Unifying data units and models in (co-)clustering. 7-31 - Sylvia Frühwirth-Schnatter

, Gertraud Malsiner-Walli:
From here to infinity: sparse finite versus Dirichlet process mixtures in model-based clustering. 33-64 - Xiaotian Zhu, David R. Hunter

:
Clustering via finite nonparametric ICA mixture models. 65-87 - Camila Borelli Zeller, Celso Rômulo Barbosa Cabral, Victor Hugo Lachos

, Luis Benites
:
Finite mixture of regression models for censored data based on scale mixtures of normal distributions. 89-116 - Daniel Fernández

, Richard Arnold, Shirley Pledger, Ivy Liu
, Roy Costilla
:
Finite mixture biclustering of discrete type multivariate data. 117-143 - Nicola Loperfido:

Finite mixtures, projection pursuit and tensor rank: a triangulation. 145-173 - Edoardo Otranto

, Massimo Mucciardi
:
Clustering space-time series: FSTAR as a flexible STAR approach. 175-199 - Diego Rivera-García

, Luis Angel García-Escudero
, Agustín Mayo-Íscar
, Joaquín Ortega
:
Robust clustering for functional data based on trimming and constraints. 201-225 - Francesca Torti

, Domenico Perrotta
, Marco Riani
, Andrea Cerioli
:
Assessing trimming methodologies for clustering linear regression data. 227-257 - Gilles Celeux, Cathy Maugis-Rabusseau

, Mohammed Sedki
:
Variable selection in model-based clustering and discriminant analysis with a regularization approach. 259-278 - Claudio Conversano

, Massimo Cannas, Francesco Mola, Emiliano Sironi
:
Random effects clustering in multilevel modeling: choosing a proper partition. 279-301 - Abby Flynt

, Nema Dean, Rebecca Nugent:
sARI: a soft agreement measure for class partitions incorporating assignment probabilities. 303-323 - Volodymyr Melnykov, Xuwen Zhu

:
Studying crime trends in the USA over the years 2000-2012. 325-341
Volume 13, Number 2, June 2019
- Editorial for issue 2/2019. 343-346

- José R. Berrendero

, Javier Cárcamo
:
Linear components of quadratic classifiers. 347-377 - José E. Chacón

:
Mixture model modal clustering. 379-404 - Dawit G. Tadesse

, Mark Carpenter:
A method for selecting the relevant dimensions for high-dimensional classification in singular vector spaces. 405-426 - Antonella Plaia

, Mariangela Sciandra:
Weighted distance-based trees for ranking data. 427-444 - Wan-Lun Wang

, Luis Mauricio Castro
, Yen-Ting Chang, Tsung-I Lin
:
Mixtures of restricted skew-t factor analyzers with common factor loadings. 445-480 - Matthijs J. Warrens

, Alexandra de Raadt:
Properties of Bangdiwala's B. 481-493 - Sébastien Loisel, Yoshio Takane

:
Comparisons among several methods for handling missing data in principal component analysis (PCA). 495-518 - Shuji Ando

, Kouji Tahata, Sadao Tomizawa:
A bivariate index vector for measuring departure from double symmetry in square contingency tables. 519-529 - Amparo Baíllo

, Javier Cárcamo, Konstantin Getman
:
New distance measures for classifying X-ray astronomy data into stellar classes. 531-557 - Christian Carmona

, Luis E. Nieto-Barajas
, Antonio Canale
:
Model-based approach for household clustering with mixed scale variables. 559-583
Volume 13, Number 3, September 2019
- Editorial for issue 3/2019. 585-589

- Aghiles Salah, Mohamed Nadif

:
Directional co-clustering. 591-620 - Toshiki Sato, Yuichi Takano, Takanobu Nakahara:

Investigating consumers' store-choice behavior via hierarchical variable selection. 621-639 - Nam-Hwui Kim

, Ryan P. Browne
:
Subspace clustering for the finite mixture of generalized hyperbolic distributions. 641-661 - Sandra Benítez-Peña

, Rafael Blanquero
, Emilio Carrizosa
, Pepa Ramírez-Cobo
:
On support vector machines under a multiple-cost scenario. 663-682 - Yu-Shan Shih

, Kuang-Hsun Liu:
Regression trees for detecting preference patterns from rank data. 683-702 - Heidi Seibold

, Torsten Hothorn
, Achim Zeileis
:
Generalised linear model trees with global additive effects. 703-725 - David Hallac

, Peter Nystrup
, Stephen P. Boyd:
Greedy Gaussian segmentation of multivariate time series. 727-751 - Zakariya Yahya Algamal

, Muhammad Hisyam Lee
:
A two-stage sparse logistic regression for optimal gene selection in high-dimensional microarray data classification. 753-771 - Alban Mbina Mbina, Guy Martial Nkiet, Fulgence Eyi Obiang

:
Variable selection in discriminant analysis for mixed continuous-binary variables and several groups. 773-795 - Waley Wei Jie Liang, Herbert K. H. Lee:

Bayesian nonstationary Gaussian process models via treed process convolutions. 797-818
Volume 13, Number 4, December 2019
- Editorial for issue 4/2019. 819-823

- Hiroyasu Abe

, Hiroshi Yadohisa
:
Orthogonal nonnegative matrix tri-factorization based on Tweedie distributions. 825-853 - Gonzalo Perez-de-la-Cruz

, Guillermina Eslava-Gomez:
Discriminant analysis for discrete variables derived from a tree-structured graphical model. 855-876 - William Cipolli III

, Timothy Hanson:
Supervised learning via smoothed Polya trees. 877-904 - Sárka Brodinová

, Peter Filzmoser
, Thomas Ortner, Christian Breiteneder, Maia Rohm:
Robust and sparse k-means clustering for high-dimensional data. 905-932 - Christian Hennig

, Willi Sauerbrei
:
Exploration of the variability of variable selection based on distances between bootstrap sample results. 933-963 - Moritz Berger

, Thomas Welchowski
, Steffen Schmitz-Valckenberg, Matthias Schmid
:
A classification tree approach for the modeling of competing risks in discrete time. 965-990 - Hosik Choi, Seokho Lee:

Convex clustering for binary data. 991-1018 - Gregor Zens

:
Bayesian shrinkage in mixture-of-experts models: identifying robust determinants of class membership. 1019-1051 - Derek S. Young

, Xi Chen
, Dilrukshi C. Hewage, Ricardo Nilo-Poyanco
:
Finite mixture-of-gamma distributions: estimation, inference, and model-based clustering. 1053-1082 - Dalia Valencia, Rosa E. Lillo

, Juan Romo
:
A Kendall correlation coefficient between functional data. 1083-1103

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