| Nome |
# |
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Multiple Correspondence K-Means: Simultaneous Versus Sequential Approach for Dimension Reduction and Clustering, file e383531d-4450-15e8-e053-a505fe0a3de9
|
281
|
|
Trusted smart statistics: The challenge of extracting usable aggregate information from new data sources, file e3835329-457a-15e8-e053-a505fe0a3de9
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254
|
|
null, file e3835322-9819-15e8-e053-a505fe0a3de9
|
241
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Partitioning predictors in multivariate regression models, file e3835317-5617-15e8-e053-a505fe0a3de9
|
221
|
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An empirical comparison of two approaches for CDPCA in high-dimensional data, file e3835329-0e20-15e8-e053-a505fe0a3de9
|
193
|
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null, file e3835322-981a-15e8-e053-a505fe0a3de9
|
172
|
|
Construction of an Immigrant Integration Composite Indicator through the Partial Least Squares Structural Equation Model K-Means, file e3835328-8bfa-15e8-e053-a505fe0a3de9
|
157
|
|
Impacted maxillary canines and root resorption of adjacent teeth: a retrospective observational study, file e3835316-3ef9-15e8-e053-a505fe0a3de9
|
119
|
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Editorial for ADAC issue 1 of volume 14 (2020), file e3835329-0e1b-15e8-e053-a505fe0a3de9
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111
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Simultaneous Supervised and Unsupervised Classification Modeling for Assessing Cluster Analysis and Improving Results Interpretability, file e3835325-5da0-15e8-e053-a505fe0a3de9
|
104
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|
A composite indicator via hierarchical disjoint factor analysis for measuring the Italian football teams’ performances, file e3835323-6988-15e8-e053-a505fe0a3de9
|
101
|
|
Dimensionality reduction via hierarchical factorial structure, file e3835324-0b1e-15e8-e053-a505fe0a3de9
|
88
|
|
Hierarchical Disjoint Non-Negative Factor Analysis: environment and waste management in the EU, file e3835323-0695-15e8-e053-a505fe0a3de9
|
83
|
|
A new hierarchical model-based composite indicator on climate change, file e3835323-04f4-15e8-e053-a505fe0a3de9
|
82
|
|
Model-based clustering with parsimonious covariance structure, file e383532c-e4cf-15e8-e053-a505fe0a3de9
|
74
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|
Differences in the clinical characteristics of COVID-19 patients who died in hospital during different phases of the pandemic: national data from Italy, file e383532b-3f7f-15e8-e053-a505fe0a3de9
|
71
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Exploring drug consumption via an ultrametric correlation matrix, file e3835327-e680-15e8-e053-a505fe0a3de9
|
64
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|
Building Well-Being Composite Indicator for Micro-Territorial Areas Through PLS-SEM and K-Means Approach, file e3835327-9932-15e8-e053-a505fe0a3de9
|
60
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|
Periodontal results of different therapeutic approaches (open vs. closed technique) and timing evaluation (< 2 year vs. > 2 year) of palatal impacted canines: a systematic review, file e383532e-013b-15e8-e053-a505fe0a3de9
|
58
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Multi-mode partitioning for text clustering to reduce dimensionality and noises, file e383531d-e5e2-15e8-e053-a505fe0a3de9
|
56
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|
Exploring drug consumption via an ultrametric correlation matrix, file e3835328-011c-15e8-e053-a505fe0a3de9
|
49
|
|
Model-based clustering with parsimonious covariance structure, file e383532c-e4ce-15e8-e053-a505fe0a3de9
|
48
|
|
A composite indicator via hierarchical disjoint factor analysis for measuring the Italian football teams’ performances, file e3835323-5913-15e8-e053-a505fe0a3de9
|
40
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|
Cladag 2017. Book of short papers, file e383531d-42a6-15e8-e053-a505fe0a3de9
|
32
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From Tandem To Simultaneous Dimensionality Reduction And Clustering Of Tourism Data, file e383531d-554a-15e8-e053-a505fe0a3de9
|
32
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A parsimonious parameterization of a nonnegative correlation matrix, file e383532d-aef1-15e8-e053-a505fe0a3de9
|
28
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Model-based clustering with parsimonious covariance structure, file e383532c-c4c8-15e8-e053-a505fe0a3de9
|
27
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A new hierarchical model-based composite indicator on climate change, file e3835323-04f5-15e8-e053-a505fe0a3de9
|
26
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Early caries detection: comparison of two procedures. A pilot study, file e3835316-6ecd-15e8-e053-a505fe0a3de9
|
24
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Hierarchical clustering and dimensionality reduction for big data, file 51581b22-efa8-42d6-8b69-65d363127f0c
|
23
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|
A new hierarchical model-based composite indicator on climate change, file e3835322-e4d9-15e8-e053-a505fe0a3de9
|
23
|
|
A composite indicator via hierarchical disjoint factor analysis for measuring the Italian football teams’ performances, file e3835323-653b-15e8-e053-a505fe0a3de9
|
23
|
|
Dimensionality reduction via hierarchical factorial structure, file e3835324-0b20-15e8-e053-a505fe0a3de9
|
20
|
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Probabilistic Disjoint Principal Component Analysis, file e383531d-fc01-15e8-e053-a505fe0a3de9
|
18
|
|
Structural equation models for simultaneous modeling of air pollutants, file 7b0dc0cc-e711-4ebd-b839-72c529668737
|
17
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|
A new hierarchical model-based composite indicator on climate change, file e3835323-04f6-15e8-e053-a505fe0a3de9
|
16
|
|
An ultrametric model to build a Composite Indicators system, file e383532e-821e-15e8-e053-a505fe0a3de9
|
15
|
|
An ultrametric model to build a Composite Indicators system, file e383532e-70a7-15e8-e053-a505fe0a3de9
|
13
|
|
Assessing environmental quality by clustering a structural equation model based index, file c0e946e0-8aca-449b-81aa-a39b30e5b6df
|
12
|
|
A composite indicator via hierarchical disjoint factor analysis for measuring the Italian football teams’ performances, file e3835323-68c6-15e8-e053-a505fe0a3de9
|
12
|
|
Objective and subjective aesthetic performance of icon® treatment for enamel hypomineralization lesions in young adolescents: a retrospective single center study, file e3835325-4f05-15e8-e053-a505fe0a3de9
|
12
|
|
Hierarchical Disjoint Non-Negative Factor Analysis: environment and waste management in the EU, file e3835323-0696-15e8-e053-a505fe0a3de9
|
11
|
|
Multivariate linear regression for heterogeneous data, file e3835311-74e0-15e8-e053-a505fe0a3de9
|
10
|
|
null, file e3835322-9231-15e8-e053-a505fe0a3de9
|
10
|
|
Exploring drug consumption via an ultrametric correlation matrix, file e3835327-f11a-15e8-e053-a505fe0a3de9
|
10
|
|
A parsimonious parameterization of a nonnegative correlation matrix, file e383532d-88b1-15e8-e053-a505fe0a3de9
|
10
|
|
Computational assessment of k-means clustering on a Structural Equation Model based index, file bb4793e0-98fd-4dec-8502-b590c1ee7a04
|
9
|
|
Finding groups in structural equation modeling through the partial least squares algorithm, file e3835325-6c07-15e8-e053-a505fe0a3de9
|
9
|
|
Exploring drug consumption via an ultrametric correlation matrix, file e3835328-011b-15e8-e053-a505fe0a3de9
|
9
|
|
The ultrametric covariance model for modelling teachers’ job satisfaction, file e383532c-4596-15e8-e053-a505fe0a3de9
|
9
|
|
A parsimonious parameterization of a nonnegative correlation matrix, file e383532d-88b0-15e8-e053-a505fe0a3de9
|
9
|
|
Non-hierarchical Classification Structures, file e3835311-7db8-15e8-e053-a505fe0a3de9
|
8
|
|
Hierarchical Disjoint Non-Negative Factor Analysis: environment and waste management in the EU, file e3835323-04f8-15e8-e053-a505fe0a3de9
|
7
|
|
Dimensionality reduction via hierarchical factorial structure, file e3835324-0b1d-15e8-e053-a505fe0a3de9
|
7
|
|
A parsimonious parameterization of a nonnegative correlation matrix, file e383532d-88af-15e8-e053-a505fe0a3de9
|
7
|
|
Dimensions of well-being and their statistical measurements, file e3835315-88df-15e8-e053-a505fe0a3de9
|
6
|
|
Skeletal Anomalies and Normal Variants in Patients with Palatally Displaced Canines, file e3835311-5db5-15e8-e053-a505fe0a3de9
|
5
|
|
Structural Classification Analysis of Three-Way Dissimilarity Data, file e3835311-dff6-15e8-e053-a505fe0a3de9
|
5
|
|
null, file e3835322-981c-15e8-e053-a505fe0a3de9
|
5
|
|
Hierarchical mixture models for biclustering in microarray data, file e3835311-6383-15e8-e053-a505fe0a3de9
|
4
|
|
Multivariate regression model based on an optimal partition of predictors., file e3835316-0310-15e8-e053-a505fe0a3de9
|
4
|
|
Hierarchical Disjoint Non-Negative Factor Analysis: environment and waste management in the EU, file e3835323-0694-15e8-e053-a505fe0a3de9
|
4
|
|
A class of two-mode clustering algorithms in a fuzzy setting, file e3835325-c8f0-15e8-e053-a505fe0a3de9
|
4
|
|
Model-based clustering with parsimonious covariance structure, file e383532c-e4d0-15e8-e053-a505fe0a3de9
|
4
|
|
An ultrametric model to build a Composite Indicators system, file e383532e-70a6-15e8-e053-a505fe0a3de9
|
4
|
|
A sella turcica bridge in subjects with dental anomalies, file e3835311-8eff-15e8-e053-a505fe0a3de9
|
3
|
|
Clustering and Dimensional Reduction for mixed variables, file e3835320-50a0-15e8-e053-a505fe0a3de9
|
3
|
|
Fuzzy clustering in a reduced subspace, file e3835325-4e6f-15e8-e053-a505fe0a3de9
|
3
|
|
The ultrametric correlation matrix for modelling hierarchical latent concepts, file e3835325-fb04-15e8-e053-a505fe0a3de9
|
3
|
|
The ultrametric covariance model for modelling teachers’ job satisfaction, file e383532c-a528-15e8-e053-a505fe0a3de9
|
3
|
|
An ultrametric model to build a Composite Indicators system, file e383532e-70a5-15e8-e053-a505fe0a3de9
|
3
|
|
null, file e383532f-0856-15e8-e053-a505fe0a3de9
|
3
|
|
Hierarchical clustering and dimensionality reduction for big data, file 1d53f9f2-cf99-4978-9f23-df8f2972fff3
|
2
|
|
Editorial for issue 4/2019, file 50668463-4011-4d83-a6eb-d8824160e803
|
2
|
|
Editorial for issue 3 2015, file 75e3d948-28a9-400f-affd-1a1a6df37188
|
2
|
|
null, file 767fe14d-5059-49b1-aea1-bd2b1c365ccd
|
2
|
|
A mixture model for the classification of three-way proximity data, file e3835311-9e88-15e8-e053-a505fe0a3de9
|
2
|
|
Dimensions of well-being and their statistical measurements, file e3835311-f745-15e8-e053-a505fe0a3de9
|
2
|
|
Disjoint factor analysis with cross-loadings, file e3835320-75cb-15e8-e053-a505fe0a3de9
|
2
|
|
Dimensionality reduction via hierarchical factorial structure, file e3835324-0b1f-15e8-e053-a505fe0a3de9
|
2
|
|
Structural Equation Modeling and simultaneous clustering through the Partial Least Squares algorithm, file e3835325-5da3-15e8-e053-a505fe0a3de9
|
2
|
|
Suicide among adolescents in Italy. A nationwide cohort study of the role of family characteristics, file e383532b-17ad-15e8-e053-a505fe0a3de9
|
2
|
|
A composite indicator for the waste management in the EU via Hierarchical Disjoint Non-Negative Factor Analysis, file e383532e-789b-15e8-e053-a505fe0a3de9
|
2
|
|
Cluster Validity Measures for Fuzzy Two-Mode Clustering, file 27ce3fef-be6b-466d-9f34-5f8b02b5a3bc
|
1
|
|
Biclustering of Gene Expression Data by an Extension of Mixtures of Factor Analyzers, file e3835311-637f-15e8-e053-a505fe0a3de9
|
1
|
|
Dimensions of well-being and their statistical measurements., file e3835312-061e-15e8-e053-a505fe0a3de9
|
1
|
|
A Mixture Model for Clustering Three-Way Proximity Data, file e3835312-621a-15e8-e053-a505fe0a3de9
|
1
|
|
Multivariate regression modeling with clustered correlated predictors, file e3835312-6f54-15e8-e053-a505fe0a3de9
|
1
|
|
Fuzzy Double Clustering: A Robust Proposal, file e3835313-49f1-15e8-e053-a505fe0a3de9
|
1
|
|
Biclustering of microarray data, file e3835315-d617-15e8-e053-a505fe0a3de9
|
1
|
|
Mixture models for simultaneous classification and reduction of three-way data, file e3835324-946b-15e8-e053-a505fe0a3de9
|
1
|
|
Editorial for issue 3/2019, file e3835324-b4d3-15e8-e053-a505fe0a3de9
|
1
|
|
Editorial for issue 2/2019, file e3835324-d213-15e8-e053-a505fe0a3de9
|
1
|
|
Editorial for issue 3/2018, file e3835324-d215-15e8-e053-a505fe0a3de9
|
1
|
|
Exploring hierarchical concepts: theoretical and application comparisons, file e3835325-e82a-15e8-e053-a505fe0a3de9
|
1
|
|
Partitioning predictors in multivariate regression models, file e383532a-a17b-15e8-e053-a505fe0a3de9
|
1
|
|
Second special issue on “Advances in latent variables: methods, models and applications”, file e383532b-570e-15e8-e053-a505fe0a3de9
|
1
|
|
The ultrametric covariance model for modelling teachers’ job satisfaction, file e383532c-4595-15e8-e053-a505fe0a3de9
|
1
|
|
The ultrametric covariance model for modelling teachers’ job satisfaction, file e383532c-a527-15e8-e053-a505fe0a3de9
|
1
|
|
Statistical Model-Based Composite Indicators for Tracking Coherent Policy Conclusions, file e383532e-7899-15e8-e053-a505fe0a3de9
|
1
|
| Totale |
3.330 |