Roberta Pappadà
Roberta Pappadà
Department of Economics, Business, Mathematics and Statistics (DEAMS) University of Trieste
Email verificata su units.it - Home page
Titolo
Citata da
Citata da
Anno
Copulas, diagonals, and tail dependence
F Durante, J Fernández-Sánchez, R Pappadà
Fuzzy Sets and Systems, Special issue on Aggregation functions at AGOP2013 …, 2015
402015
Clustering of financial time series in risky scenarios
F Durante, R Pappadà, N Torelli
Advances in Data Analysis and Classification 8 (4), 359-376, 2013
302013
Quantification of the environmental structural risk with spoiling ties: is randomization worthwhile?
R Pappadà, F Durante, G Salvadori
Stochastic Environmental Research and Risk Assessment 31 (10), 2483-2497, 2017
252017
Clustering of time series via non-parametric tail dependence estimation.
F Durante, R Pappadà, N Torelli
Statistical Papers 56 (3), 701--721, 2014
232014
Spin-off Extreme Value and Archimedean copulas for estimating the bivariate structural risk
R Pappadà, E Perrone, F Durante, G Salvadori
Stochastic Environmental Research and Risk Assessment 30 (1), 327-342, 2016
122016
Relabelling in Bayesian mixture models by pivotal units
L Egidi, R Pappada, F Pauli, N Torelli
Statistics and Computing 28 (4), 957-969, 2018
82018
Cluster analysis of time series via Kendall distribution.
F Durante, R Pappadà
Strengthening Links Between Data Analysis and Soft Computing, Advances in …, 2015
62015
Clustering of concurrent flood risks via Hazard Scenarios
R Pappadà, F Durante, G Salvadori, C De Michele
Spatial Statistics 23, 124-142, 2018
52018
Copula–based clustering methods
FML Di Lascio, F Durante, R Pappada
Copulas and Dependence Models with Applications, 49-67, 2017
42017
Maxima Units Search (MUS) algorithm: methodology and applications
L Egidi, R Pappadà, N Torelli, F Pauli
Studies in Theoretical and Applied Statistics, 2018
32018
A portfolio diversification strategy via tail dependence clustering
H Wang, R Pappadà, F Durante, E Foscolo
Soft Methods for Data Science 456, 511-518, 2017
32017
Clustering of financial time series in extreme scenarios
F Durante, R Pappadà
Atti della XLVI Riunione Scienti ca della Societ a Italiana di Statistica …, 2012
22012
pivmet: Pivotal methods for Bayesian relabelling and k-means clustering
L Egidi, R Pappada, F Pauli, N Torelli
12018
A Graphical Tool for Copula Selection Based on Tail Dependence
R Pappadà, F Durante, N Torelli
Classification,(Big) Data Analysis and Statistical Learning, 211-218, 2018
12018
K-means seeding via MUS algorithm
L Egidi, R Pappadà, F Pauli, N Torelli
Book of Short Papers SIS 2018, 2018
12018
Monitoring of microbial volatile organic compounds in traditional fermented foods: The importance of tailored approaches to optimize VOCs contribute for consumer acceptance
V Capozzi, S Makhoul, A Romano, L Cappellin, G Spano, M Scampicchio, ...
Fermented Foods: Sources, Consumption and Health Benefits, 1st ed.; Morton …, 2015
12015
Pivotal seeding for K-means based on clustering ensembles
L Egidi, R Pappada, F Pauli, N Torelli
2019
Discrimination in machine learning algorithms
R Pappadà, F Pauli
Book of Short Papers SIS 2018, 2018
2018
BITTE R
G Camuffo, HL Höger, G Seta
Facoltà di Design e Arti, Libera Università di Bolzano, 2016
2016
A semi–parametric approach in the estimation of the structural risk in environmental applications
R Pappadà, E Perrone, F Durante, G Salvadori
Proceedings of the GRASPA 2015 Conference, 1-4, 2015
2015
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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