| Titolo |
Pubblicato in |
Anno |
| Generalized Reduced K–Means |
COMPUTATIONAL STATISTICS |
2025 |
| Clustering Ordinal Data Via Parsimonious Models |
Combining, Modelling and Analyzing Imprecision, Randomness and Dependence. |
2024 |
| Mixture models for simultaneous classification and reduction of three-way data |
COMPUTATIONAL STATISTICS |
2024 |
| Functional clustering of NPLs recovery curves |
SOCIO-ECONOMIC PLANNING SCIENCES |
2024 |
| Functional projection K -means |
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS |
2024 |
| Penalized Estimation of a Finite Mixture of Linear Regression Models |
Building Bridges between Soft and Statistical Methodologies for Data Science |
2023 |
| Composite likelihood methods for parsimonious model-based clustering of mixed-type data |
ADVANCES IN DATA ANALYSIS AND CLASSIFICATION |
2023 |
| LASSO-penalized clusterwise linear regression modelling: a two-step approach |
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION |
2023 |
| Model-based simultaneous classification and reduction for three - way ordinal data |
ClaDAG2023: BOOK OF ABSTRACTS AND SHORT PAPERS |
2023 |
| Unsupervised classification of NPLs recovery curves |
IES2023: statistical methods for evaluation and quality: techniques, technologies and trends (t3) |
2023 |
| Partial membership models for soft clustering of multivariate count data |
SIS 2023 - Statistical Learning, Sustainability and Impact Evaluation. Book of the Short Papers |
2023 |
| Parsimonious and semi-constrained models for clustering mixed-type data through a composite likelihood approach |
2023 - ECOSTA Econometrics and Statistics |
2023 |
| Estimating Recovery Curve for NPLs |
MAF 2022: Mathematical and Statistical Methods for Actuarial Sciences and Finance |
2022 |
| Finite mixtures of regression models for longitudinal data |
Book of Short Papers SIS 2021 |
2021 |
| Semi-constrained model-based clustering of mixed-type data using a composite likelihood approach |
CLADAG 2021 BOOK OF ABSTRACTS AND SHORT PAPERS : 13th Scientific Meeting of the Classification and Data Analysis Group Firenze, September 9-11, 2021 |
2021 |
| Penalized Versus Constrained Approaches for Clusterwise Linear Regression Modeling |
Studies in Classification, Data Analysis, and Knowledge Organization |
2021 |
| A Comparison Between Methods to Cluster Mixed-Type Data: Gaussian Mixtures Versus Gower Distance |
Studies in Classification, Data Analysis, and Knowledge Organization |
2021 |
| Lasso-penalized clusterwise linear regression modeling with a two–step approach |
Models and Learning for Clustering and Classification |
2021 |
| Mixture of factor analyzers for mixed-type data via a composite likelihood approach |
Models and Learning for Clustering and Classification |
2021 |
| Factor Uniqueness of the Structural Parafac Model |
PSYCHOMETRIKA |
2020 |
