Advances in Data Analysis and Classification
2008 - 2026
Current editor(s): H.-H. Bock, W. Gaul, A. Okada, M. Vichi and C. Weihs From: Springer German Classification Society - Gesellschaft für Klassifikation (GfKl) Japanese Classification Society (JCS) Classification and Data Analysis Group of the Italian Statistical Society (CLADAG) International Federation of Classification Societies (IFCS) Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing (). Access Statistics for this journal.
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Volume 20, issue 1, 2026
- Editorial for ADAC issue 1 of volume 20 (2026) pp. 1-9

- Berthold Lausen and Maurizio Vichi
- Mixtures of regressions using matrix-variate heavy-tailed distributions pp. 11-38

- Salvatore D. Tomarchio and Michael P. B. Gallaugher
- Robust gradient boosting for generalized additive models for location, scale and shape pp. 39-58

- Jan Speller, Christian Staerk, Francisco Gude and Andreas Mayr
- A probabilistic method for reconstructing the Foreign Direct Investments network in search of ultimate host economies pp. 59-79

- Nadia Accoto, Valerio Astuti and Costanza Catalano
- Entropy-based fuzzy clustering of interval-valued time series pp. 81-107

- Vincenzina Vitale, Pierpaolo D’Urso, Livia De Giovanni and Raffaele Mattera
- Scalable Bayesian p-generalized probit and logistic regression pp. 109-143

- Zeyu Ding, Simon Omlor, Katja Ickstadt and Alexander Munteanu
- Calibrated kNN classification via second-layer neighborhood analysis pp. 145-165

- Bastian Pfeifer and Markus Kreuzthaler
- Unsupervised learning from attributed networks pp. 167-196

- Lazhar Labiod and Mohamed Nadif
- Identifying influential observations in concurrent functional regression with weighted bootstrap pp. 197-226

- Ryan D. Pittman and David B. Hitchcock
- Structural equation modeling with factors and composites within the framework of the basic design pp. 227-254

- Arthur Tenenhaus, Michel Tenenhaus and Theo K. Dijkstra
- Classification of multivariate count data with multivariate log-linear conditional Poisson distribution pp. 255-288

- Juan M. Muñoz-Pichardo and Rafael Pino-Mejías
- Directional density-based clustering pp. 289-314

- Paula Saavedra-Nieves and Martín Fernández-Pérez
Volume 19, issue 4, 2025
- Editorial for ADAC issue 4 of volume 19 (2025) pp. 855-859

- Maurizio Vichi, Andrea Cerioli and Hans A. Kestler
- Using Bagging to improve clustering methods in the context of three-dimensional shapes pp. 861-893

- Inácio Nascimento, Raydonal Ospina and Getúlio Amorim
- Marginal models with individual-specific effects for the analysis of longitudinal bipartite networks pp. 895-920

- Francesco Bartolucci, Antonietta Mira and Stefano Peluso
- Robust Bayesian inference for the censored mixture of experts model using heavy-tailed distributions pp. 921-949

- Elham Mirfarah, Mehrdad Naderi, Tsung-I Lin and Wan-Lun Wang
- A sparse exponential family latent block model for co-clustering pp. 951-987

- Saeid Hoseinipour, Mina Aminghafari, Adel Mohammadpour and Mohamed Nadif
- Characterisation and calibration of multiversal methods pp. 989-1021

- Giulio Giacomo Cantone and Venera Tomaselli
- Addressing class imbalance in functional data clustering pp. 1023-1050

- Catherine Higgins and Michelle Carey
- Unsupervised curve clustering using wavelets pp. 1051-1085

- Umberto Amato, Anestis Antoniadis, Italia De Feis and Irène Gijbels
- Reducing the dimensionality and granularity in hierarchical categorical variables pp. 1087-1118

- Paul Wilsens, Katrien Antonio and Gerda Claeskens
- Parametric models for distributional data pp. 1119-1146

- Paula Brito and A. Pedro Duarte Silva
- Correction: Characterisation and calibration of multiversal methods pp. 1147-1147

- Giulio Giacomo Cantone and Venera Tomaselli
Volume 19, issue 3, 2025
- Editorial for ADAC issue 3 of volume 19 (2025) pp. 545-549

- Maurizio Vichi, Andrea Cerioli and Hans A. Kestler
- Clustering ensemble extraction: a knowledge reuse framework pp. 551-578

- Mohaddeseh Sedghi, Ebrahim Akbari, Homayun Motameni and Touraj Banirostam
- View selection in multi-view stacking: choosing the meta-learner pp. 579-617

- Wouter Loon, Marjolein Fokkema, Botond Szabo and Mark Rooij
- Comparison of internal evaluation criteria in hierarchical clustering of categorical data pp. 619-648

- Zdenek Sulc, Jaroslav Hornicek, Hana Rezankova and Jana Cibulkova
- Multidimensional scaling for big data pp. 649-670

- Pedro Delicado and Cristian Pachón-García
- Clustering functional data via variational inference pp. 671-720

- Chengqian Xian, Camila P. E. Souza, John Jewell and Ronaldo Dias
- A two-group canonical variate analysis biplot for an optimal display of both means and cases pp. 721-748

- Niel Roux and Sugnet Gardner-Lubbe
- Clustering large mixed-type data with ordinal variables pp. 749-767

- Gero Szepannek, Rabea Aschenbruck and Adalbert Wilhelm
- Natural language processing and financial markets: semi-supervised modelling of coronavirus and economic news pp. 769-793

- Carlos Moreno-Pérez and Marco Minozzo
- Dirichlet compound negative multinomial mixture models and applications pp. 795-830

- Ornela Bregu and Nizar Bouguila
- On some properties of Cronbach’s α coefficient for interval-valued data in questionnaires pp. 831-854

- José García-García, María Ángeles Gil and María Asunción Lubiano
Volume 19, issue 2, 2025
- Special issue on “Advances in clustering, classification and related methods” pp. 271-273

- Paolo Giordani, Christian Hennig, Julien Jacques and Carla Rampichini
- Asymmetric Laplace scale mixtures for the distribution of cryptocurrency returns pp. 275-322

- Antonio Punzo and Luca Bagnato
- A consensus-constrained parsimonious Gaussian mixture model for clustering hyperspectral images pp. 323-359

- Ganesh Babu, Aoife Gowen, Michael Fop and Isobel Claire Gormley
- Random models for adjusting fuzzy rand index extensions pp. 361-385

- Ryan DeWolfe and Jeffrey L. Andrews
- Clustering and classification of spatio-temporal data using spatial dynamic panel data models pp. 387-435

- Giuseppe Feo, Francesco Giordano, Sara Milito, Marcella Niglio and Maria Lucia Parrella
- Increasing biases can be more efficient than increasing weights pp. 437-468

- Carlo Metta, Marco Fantozzi, Andrea Papini, Gianluca Amato, Matteo Bergamaschi, Andrea Fois, Silvia Giulia Galfrè, Alessandro Marchetti, Michelangelo Vegliò, Maurizio Parton and Francesco Morandin
- Variational inference for estimating dynamic stochastic block models through an evolutionary algorithm pp. 469-492

- Luca Brusa and Fulvia Pennoni
- Comparing flexible modelling approaches: the varying-thresholds model versus quantile regression pp. 493-514

- Niccolò Ducci, Leonardo Grilli and Marta Pittavino
- When non-response makes estimates from a census a small area estimation problem: the case of the survey on graduates’ employment status in Italy pp. 515-543

- Maria Giovanna Ranalli, Fulvia Pennoni, Francesco Bartolucci and Antonietta Mira
Volume 19, issue 1, 2025
- Editorial for ADAC issue 1 of volume 19 (2025) pp. 1-4

- Maurizio Vichi, Andrea Cerioli and Hans A. Kestler
- Loss-guided stability selection pp. 5-30

- Tino Werner
- QDA classification of high-dimensional data with rare and weak signals pp. 31-65

- Hanning Chen, Qiang Zhao and Jingjing Wu
- RGA: a unified measure of predictive accuracy pp. 67-93

- Paolo Giudici and Emanuela Raffinetti
- k-means clustering for persistent homology pp. 95-119

- Yueqi Cao, Prudence Leung and Anthea Monod
- Robust functional logistic regression pp. 121-145

- Berkay Akturk, Ufuk Beyaztas, Han Lin Shang and Abhijit Mandal
- Spatial quantile clustering of climate data pp. 147-175

- Carlo Gaetan, Paolo Girardi and Victor Muthama Musau
- Estimators of various kappa coefficients based on the unbiased estimator of the expected index of agreements pp. 177-207

- A. Martín Andrés and M. Álvarez Hernández
- Choosing the number of factors in factor analysis with incomplete data via a novel hierarchical Bayesian information criterion pp. 209-235

- Jianhua Zhao, Changchun Shang, Shulan Li, Ling Xin and Philip L. H. Yu
- Clustering by deep latent position model with graph convolutional network pp. 237-270

- Dingge Liang, Marco Corneli, Charles Bouveyron and Pierre Latouche
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