CLADAG PROGRAM October 8, 2015<\/p>\n
08.00 – 09. 00\u00a0\u00a0 REGISTRATION<\/p>\n
09.00 – 09. 30\u00a0\u00a0 OPENING CEREMONY<\/p>\n
09.30 – 10. 20\u00a0\u00a0 KEY1\u00a0\u00a0 KEYNOTE1 – Chair: N. Torelli\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Nautilus Room<\/p>\n
Mining Text Networks\u00a0\u00a0 D. Banks<\/p>\n
10.20 – 10. 50\u00a0\u00a0 COFFEE BREAK<\/p>\n
10.50 – 12. 05\u00a0\u00a0 SPEC1 Robust methods for the analysis of Economic (Big) data\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Nautilus Room<\/p>\n
Chair: S. Salini – Discussant: L.A. Grac\u00eca-Escudero<\/p>\n
Fast and Robust Seemingly Unrelated Regression – M. Hubert, T. Verdonck, O. Yorulmaz<\/p>\n
Application to the detection of customs fraud of the goodness-of-fit testing for the Newcomb-Benford law – A. Cerioli, L. Barabesi, A. Cerasa, D. Perrotta<\/p>\n
Monitoring the robust analysis of a single multivariate sample – M. Riani, A. Atkinson, A. Cerioli<\/p>\n
10.50 – 12. 05\u00a0\u00a0 SPEC2 Bayesian nonparametric clustering\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Cyprea Room<\/p>\n
Chair: R. Rotondi – Discussant: M. Trevisani<\/p>\n
A Bayesian nonparametric approach to model association between clusters of SNPs and disease responses – R. Argiento, A. Guglielmi, C.K. Hsiao, F. Ruggeri, C. Wang<\/p>\n
A Bayesian nonparametric model for clustering and borrowing information – B. Nipoti, A. Lijoi, I. Pruenster<\/p>\n
Sequential clustering based on Dirichlet process priors – S. Tonellato, R. Casarin, A. Pastore<\/p>\n
12.05 – 13. 05\u00a0\u00a0 SOL1 Advances in Density-based clustering\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Nautilus Room<\/p>\n
Chair: F. Greselin<\/p>\n
A nonparametric clustering method for image segmentation – G. Menardi<\/p>\n
Robust clustering for heterogeneous skew data – A. Mayo Iscar, L.A. Garc\u00eca-Escudero, F. Greselin<\/p>\n
Regularizing finite mixtures of Gaussian distributions – B. Gr\u00fcn, G. Malsiner-Walli<\/p>\n
12.05 – 13. 05\u00a0\u00a0 SOL2 Latent variable models for longitudinal data – Part I\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Cyprea Room<\/p>\n
Chair: S. Bacci<\/p>\n
A joint model for longitudinal and survival data based on an AR(1) latent process – S. Pandolfi, S. Bacci, F. Bartolucci<\/p>\n
Finite mixture models for mixed data: EM algorithms and PARAFC representations – M. Alf\u00f2, P. Giordani<\/p>\n
On the use of the contaminated Gaussian distribution in Hidden Markov models for longitudinal data – A. Punzo, A. Maruotti<\/p>\n
12.05 – 13. 05\u00a0\u00a0 CONTR1 Functional data analysis\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Astrea Room<\/p>\n
Chair: C. Weihs<\/p>\n
A generalized distance for inference on functional data – A. Ghiglietti, A.M. Pagagnoni<\/p>\n
Long gaps in multivariate spatio-temporal data: an approach based on Functional Data Analysis – A. Plaia, M. Ruggeri, F. Di Salvo<\/p>\n
Effects on curve clustering of different transformations of chronological textual data – M. Trevisani, A. Tuzzi<\/p>\n
12.05 – 13. 05\u00a0\u00a0 CONTR2 Robustness and data diagnostics I\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Alvania Room<\/p>\n
Chair: A. Cerioli<\/p>\n
A note on the reliability of a classifier – L. Frigau<\/p>\n
Robust classification for multivariate functional data – F. Ieva, A.M. Pagagnoni<\/p>\n
Size control of robust regression estimators – S. Salini, A. Cerioli, F. Laurini, M. Riani<\/p>\n
13.05 – 14. 30\u00a0\u00a0 LUNCH<\/p>\n
14.30 – 15. 30\u00a0\u00a0 SOL3 Latent variable models for longitudinal data – Part II\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0Nautilus Room<\/p>\n
Chair: F. Bartolucci<\/p>\n
A hidden Markov approach to the analysis of incomplete multivariate longitudinal data – F. Lagona<\/p>\n
Latent Markov and Growth Mixture models: a comparison – F. Pennoni, I. Romeo<\/p>\n
Latent worths and longitudinal paired comparisons \u2013 a Markov model of dependence – B. Francis, A. Grans, R. Dittrich<\/p>\n
14.30 – 15. 30\u00a0\u00a0 SOL4 Multivariate data analysis in environmental sciences\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Cyprea Room<\/p>\n
Chair: R. Argiento<\/p>\n
Multivariate downscaling for non-Gaussian data – L. Paci, D. Cocchi, C. Trivisano<\/p>\n
Multivariate spatio temporal models for large datasets and joint exposure to airborne multipollutants in Europe – A. Fass\u00f2, F. Finazzi, F. Ndongo<\/p>\n
Clustering macroseismic fields by statistical data depth functions – R. Rotondi, C. Agostinelli, E. Varini<\/p>\n
14.30 – 15. 30\u00a0\u00a0 CONTR3 Data Mining\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Astrea Room<\/p>\n
Chair: P. Mariani<\/p>\n
The movements of emotions: an exploratory classification on affective movement data – P. Dente, A. Kappas, A.F.X. Wilhelm<\/p>\n
Electre tri-machine learning approach to the record linkage problem – V. Minnetti, R. De Leone<\/p>\n
Quality of Classification approaches for the quantitative analysis of international conflict – A.F.X. Wilhelm<\/p>\n
14.30 – 15. 30\u00a0\u00a0 CONTR4 Clustering models \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0Alvania Room<\/p>\n
Chair: F. Leisch<\/p>\n
The rtclust Procedure for Robust Clustering – F. Dotto, A. Farcomeni, L.A. Garc\u00eca-Escudero, A. Mayo-Iscar<\/p>\n
What are the true clusters? – C. Hennig<\/p>\n
A novel model-based clustering approach for massive datasets of spatially registered time series. With application to sea surface temperature remote sensing data – F. Finazzi, M. Scott<\/p>\n
15.30 – 16. 45\u00a0\u00a0 SPEC3 Causal Inference with Complex Data Structures \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0Nautilus Room<\/p>\n
Chair: A. Mattei – Discussant: L. Grilli<\/p>\n
A novel model-based clustering approach for massive datasets of spatially registered time series. With application to sea surface temperature remote sensing data – M. Baccini, A. Mattei, F. Mealli<\/p>\n
Identification and Estimation of Causal Mechanisms in Clustered Encouragement Designs: Disentangling Bed Nets using Bayesian Principal Stratification – L. Forastiere, F. Mealli, T. Van der Weele<\/p>\n
The effects of a dropout prevention program on secondary students \u2019 outcomes – A. Mattei, E. Conti, S. Duranti, F. Mealli, N. Sciclone<\/p>\n
15.30 – 16. 45\u00a0\u00a0 SPEC4 Clustering in time series\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Cyprea Room<\/p>\n
Chair: M. La Rocca – Discussant: P. Coretto<\/p>\n
Probabilistic boosted-oriented clustering of time series – R. Siciliano, A. D’Ambrosio, G. Frasso, C. Iorio<\/p>\n
Copula-based fuzzy clustering of time series – F. Durante, P. D’Urso<\/p>\n
Comparing multi-step ahead forecasting functions for time series clustering – M. Corduas, G. Ragozini<\/p>\n
16.45 – 17. 15\u00a0\u00a0 COFFEE BREAK<\/p>\n
17.15 – 18. 15\u00a0\u00a0 SOL5 Advanced models for tourism analysis\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Nautilus Room<\/p>\n
Chair: S. Mignani<\/p>\n
Analysing territorial heterogeneity in tourists\u2019 satisfaction towards Italian destinations – C. Bernini, A. Cerqua, G. Pellegrini<\/p>\n
Micro-economc determinants of Tourist Expenditure: a Quantile Regression Approach – E. Marrocu, R. Paci, A. Zara<\/p>\n
Inequalities and tourism consumption behaviour: a mixture model analysis – M.F. Cracolici, C. Bernini, C. Viroli<\/p>\n
17.15 – 18. 15\u00a0\u00a0 SOL6 Bayesian Networks and Graphical Models in Socio-Economic Sciences\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Cyprea Room<\/p>\n
Chair: P. Vicard<\/p>\n
Bayesian Networks for Firm Performance Evaluation – C. Tarantola, M.E. De Giuli, P. Gottardo, A.M. Moisello<\/p>\n
Graphical model using copula for measurement error modeling – D. Marella, P. Vicard<\/p>\n
17.15 – 18. 15\u00a0\u00a0 CONTR5 Big Data Analysis\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Astrea Room<\/p>\n
Chair: C. Conversano<\/p>\n
Big Data Classification: Simulations in the many features case – C. Weihs<\/p>\n
From Big Data to information: statistical issues through examples – S. Signorelli, S. Biffignandi<\/p>\n
Big data meet pharmaceutical industry: an application on social media data – P. Mariani, C. Liberati<\/p>\n
17.15 – 18. 15\u00a0\u00a0 CONTR6 Discrimination and Classification\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Alvania Room<\/p>\n
Chair: B. Gr\u00fcn<\/p>\n
Defining the subjects distance in hierarchical cluster analysis by copula approach – M. Nai Ruscone, A. Bonanomi, S.A. Osmetti<\/p>\n
Supervised classification of defective crankshafts by image analysis – J. Tarr\u00edo Saavedra, B. Remeseiro, M. Francisco Fern\u00e1ndez, M. Gonz\u00e1lez Penedo, S. Naya, R. Cao<\/p>\n
Archetypal analysis for data-driven prototype identification – G. Ragozini, F. Palumbo, M.R. D’Esposito<\/p>\n
18.30 – 20. 00\u00a0\u00a0 WELCOME COCKTAIL<\/p>\n
<\/p>\n","protected":false},"excerpt":{"rendered":"
CLADAG PROGRAM October 8, 2015 08.00 – 09. 00\u00a0\u00a0 REGISTRATION 09.00 – 09. 30\u00a0\u00a0 OPENING CEREMONY 09.30 – 10. 20\u00a0\u00a0 KEY1\u00a0\u00a0 KEYNOTE1 – Chair: N. Torelli\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Nautilus Room Mining Text Networks\u00a0\u00a0 D. Banks 10.20 – 10. 50\u00a0\u00a0 COFFEE BREAK 10.50 – 12. 05\u00a0\u00a0 SPEC1 Robust methods for the analysis of Economic (Big) data\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Nautilus Room […]<\/a><\/p>\n","protected":false},"author":1858,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-559","page","type-page","status-publish","hentry","post-seq-1","post-parity-odd","meta-position-corners","fix"],"_links":{"self":[{"href":"https:\/\/convegni.unica.it\/cladag2015\/wp-json\/wp\/v2\/pages\/559","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/convegni.unica.it\/cladag2015\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/convegni.unica.it\/cladag2015\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/convegni.unica.it\/cladag2015\/wp-json\/wp\/v2\/users\/1858"}],"replies":[{"embeddable":true,"href":"https:\/\/convegni.unica.it\/cladag2015\/wp-json\/wp\/v2\/comments?post=559"}],"version-history":[{"count":10,"href":"https:\/\/convegni.unica.it\/cladag2015\/wp-json\/wp\/v2\/pages\/559\/revisions"}],"predecessor-version":[{"id":1090,"href":"https:\/\/convegni.unica.it\/cladag2015\/wp-json\/wp\/v2\/pages\/559\/revisions\/1090"}],"wp:attachment":[{"href":"https:\/\/convegni.unica.it\/cladag2015\/wp-json\/wp\/v2\/media?parent=559"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}