Publications @Statistics

Bortolotti, T. , Peli, R. , Lanzano, G. , Sgobba, S. , Menafoglio, A. (2024).
Weighted Functional Data Analysis for the Calibration of a Ground Motion Model in Italy, Journal of the American Statistical Association, 1-12.

Calissano, A. , Feragen, A. , Vantini, S. (2024).
Populations of unlabelled networks: graph space geometry and generalized geodesic principal components, Biometrika, vol. 111(1), 147-170.

Fabris, E. , Boldrin, C. , Gregorio, C. , Pezzato, A. , Gagno, G. , Giannini, F. , et al (2024).
The Prognostic impact of treatments evolution in STEMI, International Journal of Cardiology, vol. 394, 131352.

Mandigers, T. J. , Fulgheri, I. , Pugliese, G. , Bissacco, D. , Savarè, L. , Ieva, F. , et al (2024).
Patients’ Radiation Exposure During Endovascular Abdominal Aortic Aneurysm Repair, Annals of Vascular Surgery, vol. 98, 115-123.

Masci, C. , Ieva, F. , Paganoni, A. M. (2024).
Inferential Tools for Assessing Dependence Across Response Categories in Multinomial Models with Discrete Random Effects, Journal of Classification.

Palummo, A. , Arnone, E. , Formaggia, L. , Sangalli, L. M. (2024).
Functional principal component analysis for incomplete space–time data, Environmental and Ecological Statistics.

Ragni, A. , Ippolito, D. , Masci, C. (2024).
Assessing the impact of hybrid teaching on students’ academic performance via multilevel propensity score-based techniques, Socio-Economic Planning Sciences, vol. 92, 101824.

Setti, M. , Merlo, M. , Gigli, M. , Munaretto, L. , Paldino, A. , Stolfo, D. , et al (2024).
Role of arrhythmic phenotype in prognostic stratification and management of dilated cardiomyopathy, European Journal of Heart Failure.

Sgobba, S. , Felicetta, C. , Bortolotti, T. , Menafoglio, A. , Lanzano, G. , Pacor, F. (2024).
A geostatistical modelling of empirical amplification functions and related site proxies for shaking scenarios in central Italy, Soil Dynamics and Earthquake Engineering, vol. 179, 108496.

Stolfo, D. , Pagnesi, M. , Chiarito, M. , Baldetti, L. , Merlo, M. , Lombardi, C. M. , et al (2024).
Clinical burden and predictors of non-cardiovascular mortality and morbidity in advanced heart failure, The Journal of Heart and Lung Transplantation, vol. 43(4), 554-562.

Abramowicz, K. , Pini, A. , Schelin, L. , Sjöstedt de Luna, S. , Stamm, A. , Vantini, S. (2023).
Domain selection and familywise error rate for functional data: A unified framework, Biometrics, vol. 79(2), 1119-1132.

Ajroldi, N. , Diquigiovanni, J. , Fontana, M. , Vantini, S. (2023).
Conformal prediction bands for two-dimensional functional time series, Computational Statistics & Data Analysis, vol. 187, 107821.

Archetti, A. , Ieva, F. , Matteucci, M. (2023).
Scaling survival analysis in healthcare with federated survival forests: A comparative study on heart failure and breast cancer genomics, Future Generation Computer Systems, vol. 149, 343-358.

Arnone, E. , Sangalli, L. M. , Vicini, A. (2023).
Smoothing spatio-temporal data with complex missing data patterns, Statistical Modelling, vol. 23(4), 327-356.

Arnone, E. , Negri, L. , Panzica, F. , Sangalli, L. M. (2023).
Analyzing data in complicated 3D domains: Smoothing, semiparametric regression, and functional principal component analysis, Biometrics, vol. 79, 3510-3521.

Arnone, E. , De Falco, C. , Formaggia, L. , Meretti, G. , Sangalli, L. M. (2023).
Computationally efficient techniques for spatial regression with differential regularization, International Journal of Computer Mathematics, vol. 100(10), 1971-1991.

Baldassarre, D. , Iacoviello, L. , Baetta, R. , Roncaglioni, M. C. , Condorelli, G. , Remuzzi, G. , et al (2023).
Rationale and design of the CV-PREVITAL study: an Italian multiple cohort randomised controlled trial investigating innovative digital strategies in primary cardiovascular prevention, BMJ Open, vol. 13(7), e072040.

Barbi, C. , Menafoglio, A. , Secchi, P. (2023).
An object-oriented approach to the analysis of spatial complex data over stream-network domains, Spatial Statistics, vol. 58, 100784.

Benedetti, L. , Boniardi, E. , Chiani, L. , Ghirri, J. , Mastropietro, M. , Cappozzo, A. , et al (2023).
Variational inference for semiparametric Bayesian novelty detection in large datasets, Advances in Data Analysis and Classification.

Bertoletti, A. , Cannistrà, M. , Diaz Lema, M. , Masci, C. , Mergoni, A. , Rossi, L. , et al (2023).
The Determinants of Mathematics Achievement: A Gender Perspective Using Multilevel Random Forest, Economies, vol. 11(2), 32.

Capezza, C. , Centofanti, F. , Lepore, A. , Menafoglio, A. , Palumbo, B. , Vantini, S. (2023).
funcharts: control charts for multivariate functional data in R, Journal of Quality Technology, vol. 55(5), 566-583.

Cappozzo, A. , Ieva, F. , Fiorito, G. (2023).
A general framework for penalized mixed-effects multitask learning with applications on DNA methylation surrogate biomarkers creation, The Annals of Applied Statistics, vol. 17(4), 3257-3282.

Cappozzo, A. , García-Escudero, L. A. , Greselin, F. , Mayo-Iscar, A. (2023).
Graphical and Computational Tools to Guide Parameter Choice for the Cluster Weighted Robust Model, Journal of Computational and Graphical Statistics, vol. 32(3), 1195-1214.

Cavinato, L. , Sollini, M. , Ragni, A. , Bartoli, F. , Zanca, R. , Pasqualetti, F. , et al (2023).
Radiomics-Based Inter-Lesion Relation Network to Describe [18F]FMCH PET/CT Imaging Phenotypes in Prostate Cancer, Cancers, vol. 15(3), 823.

Cavinato, L. , Gozzi, N. , Sollini, M. , Kirienko, M. , Carlo-Stella, C. , Rusconi, C. , et al (2023).
Explainable domain transfer of distant supervised cancer subtyping model via imaging-based rules extraction, Artificial Intelligence in Medicine, vol. 138, 102522.

Cavinato, L. , Massi, M. C. , Sollini, M. , Kirienko, M. , Ieva, F. (2023).
Dual adversarial deconfounding autoencoder for joint batch-effects removal from multi-center and multi-scanner radiomics data, Scientific Reports, vol. 13(1).

Centofanti, F. , Lepore, A. , Menafoglio, A. , Palumbo, B. , Vantini, S. (2023).
Adaptive smoothing spline estimator for the function-on-function linear regression model, Computational Statistics, vol. 38(1), 191-216.

Clementi, L. , Arnone, E. , Santambrogio, M. D. , Franceschetti, S. , Panzica, F. , Sangalli, L. M. (2023).
Anatomically compliant modes of variations: New tools for brain connectivity, PLOS ONE, vol. 18(11), e0292450.

Costa, G. , Cavinato, L. , Fiz, F. , Sollini, M. , Chiti, A. , Torzilli, G. , et al (2023).
Mapping Tumor Heterogeneity via Local Entropy Assessment: Making Biomarkers Visible, Journal of Digital Imaging, vol. 36(3), 1038-1048.

Di Iorio, J. , Vantini, S. (2023).
funLOCI: A Local Clustering Algorithm for Functional Data, Journal of Classification.

Elías, A. , Jiménez, R. , Paganoni, A. M. , Sangalli, L. M. (2023).
Integrated Depths for Partially Observed Functional Data, Journal of Computational and Graphical Statistics, vol. 32(2), 341-352.

Ferraccioli, F. , Sangalli, L. M. , Finos, L. (2023).
Nonparametric tests for semiparametric regression models, TEST, vol. 32(3), 1106-1130.

Fiz, F. , Rossi, N. , Langella, S. , Ruzzenente, A. , Serenari, M. , Ardito, F. , et al (2023).
Radiomic Analysis of Intrahepatic Cholangiocarcinoma: Non-Invasive Prediction of Pathology Data: A Multicenter Study to Develop a Clinical–Radiomic Model, Cancers, vol. 15(17), 4204.

Fontana, M. , Zeni, G. , Vantini, S. (2023).
Conformal prediction: A unified review of theory and new challenges, Bernoulli, vol. 29(1), 1-23.

Gatti, F. , Bonaventura, L. , Menafoglio, A. , Papini, M. , Longoni, L. (2023).
A fully coupled superficial runoff and soil erosion basin scale model with efficient time stepping, Computers & Geosciences, vol. 177, 105362.

Hron, K. , Machalová, J. , Menafoglio, A. (2023).
Bivariate densities in Bayes spaces: orthogonal decomposition and spline representation, Statistical Papers, vol. 64(5), 1629-1667.

Masci, C. , Cannistrà, M. , Mussida, P. (2023).
Modelling time-to-dropout via shared frailty Cox models. A trade-off between accurate and early predictions, Studies in Higher Education, 1-19.

Massi, M. C. , Franco, N. R. , Manzoni, A. , Paganoni, A. M. , Park, H. A. , Hoffmeister, M. , et al (2023).
Learning high-order interactions for polygenic risk prediction, PLOS ONE, vol. 18(2), e0281618.

Merlo, I. , Crea, M. , Berta, P. , Ieva, F. , Carle, F. , Rea, F. , et al (2023).
Detecting early signals of COVID-19 outbreaks in 2020 in small areas by monitoring healthcare utilisation databases: first lessons learned from the Italian Alert_CoV project, Eurosurveillance, vol. 28(1).

Nicolussi, F. , Cazzaro, M. , Rudas, T. (2023).
Improving the power of hypothesis tests in sparse contingency tables, Statistical Papers.

Nuzzi, V. , Cannatà, A. , Pellicori, P. , Manca, P. , Stolfo, D. , Gregorio, C. , et al (2023).
Diuretic dose trajectories in dilated cardiomyopathy: prognostic implications, Clinical Research in Cardiology, vol. 112(3), 419-430.

Nuzzi, V. , Raafs, A. , Manca, P. , Henkens, M. T. , Gregorio, C. , Boscutti, A. , et al (2023).
Left Atrial Reverse Remodeling in Dilated Cardiomyopathy, Journal of the American Society of Echocardiography, vol. 36(2), 154-162.

Pezzato, A. , Fabris, E. , Gregorio, C. , Cittar, M. , Contessi, S. , Carriere, C. , et al (2023).
Implantable-cardioverter-defibrillator after ST-elevation myocardial infarction: when and how frequently is it implanted and what is the rate of appropriate interventions? Insight from Trieste registry, Journal of Cardiovascular Medicine, vol. 24(12), 871-879.

Pidó, S. , Pinoli, P. , Crovari, P. , Ieva, F. , Garzotto, F. , Ceri, S. (2023).
Ask Your Data—Supporting Data Science Processes by Combining AutoML and Conversational Interfaces, IEEE Access, vol. 11, 45972-45988.

Pini, A. , Sørensen, H. , Tolver, A. , Vantini, S. (2023).
Local inference for functional linear mixed models, Computational Statistics & Data Analysis, vol. 181, 107688.

Savaré, L. , Ieva, F. , Corrao, G. , Lora, A. (2023).
Capturing the variety of clinical pathways in patients with schizophrenic disorders through state sequences analysis, BMC Medical Research Methodology, vol. 23(1).

Serafini, L. , Gottlob, A. , Pierri, F. , Ieva, F. , Ceri, S. (2023).
Risk Narratives on Immigration During the COVID-19 Crisis in Italy: A Comparative Analysis of Facebook Posts Published by Politicians and by News media, Journal of Communication Inquiry, 019685992311679.

Spreafico, M. , Ieva, F. , Fiocco, M. (2023).
Modelling time-varying covariates effect on survival via functional data analysis: application to the MRC BO06 trial in osteosarcoma, Statistical Methods & Applications, vol. 32(1), 271-298.

Zecchin, M. , Trevisan, B. , Baggio, C. , Bessi, R. , Saitta, M. , Salvatore, L. , et al (2023).
Short- and long-term survival in patients over 90 years old undergoing pacemaker implantation, Journal of Cardiovascular Medicine, vol. 24(9), 625-630.

Abramowicz, K., Pini, A., Schelin, L., Sjöstedt de Luna, S., Stamm, A., Vantini, S. (2022).
Domain selection and familywise error rate for functional data: A unified framework, Biometrics.

Arnone, E., Ferraccioli, F., Pigolotti, C., Sangalli, L.M. (2022).
A roughness penalty approach to estimate densities over two-dimensional manifolds, Computational Statistics and Data Analysis, art no 10752.

Bastian, D., Gregorio, C., Buia, V., Walaschek, J., Rittger, H., Vitali-Serdoz, L. (2022).
His bundle pacing guided by automated intrinsic morphology matching is feasible in patients with narrow QRS complexes, Scientific Reports, vol. 12(1), art no 360.

Belli, E., Vantini, S. (2022).
Measure inducing classification and regression trees for functional data, Statistical Analysis and Data Mining, vol. 15(5), pp. 553-569.

Belli, E., Vantini, S. (2022).
Ridge regression with adaptive additive rectangles and other piecewise functional templates, Neurocomputing, pp. 328-34.

Calissano, A., Feragen, A., Vantini, S. (2022).
Graph-valued regression: Prediction of unlabelled networks in a non-Euclidean graph space, Journal of Multivariate Analysis, art no 104950.

Cannistrà, M., Masci, C., Ieva, F., Agasisti, T., Paganoni, A.M. (2022).
Early-predicting dropout of university students: an application of innovative multilevel machine learning and statistical techniques, Studies in Higher Education, vol. 47(9), pp. 1935-1956.

Capezza, C., Centofanti, F., Lepore, A., Menafoglio, A., Palumbo, B., Vantini, S. (2022).
Functional regression control chart for monitoring ship CO2 emissions, Quality and Reliability Engineering International, vol. 38(3), pp. 1519-1537.

Cappozzo, A., McCrory, C., Robinson, O., Freni Sterrantino, A., Sacerdote, C., Krogh, V., et al (2022).
A blood DNA methylation biomarker for predicting short-term risk of cardiovascular events, Clinical Epigenetics, vol. 14(1), art no 12.

Caramenti, L., Menafoglio, A., Sgobba, S., Lanzano, G. (2022).
Multi-source geographically weighted regression for regionalized ground-motion models, Spatial Statistics, art no 100610.

Casa, A., Cappozzo, A., Fop, M. (2022).
Group-Wise Shrinkage Estimation in Penalized Model-Based Clustering, Journal of Classification, vol. 39(3), pp. 648-67.

Cavinato, L., Pegoraro, M., Ragni, A., Ieva, F. (2022).
Imaging-based representation and stratification of intra-tumor heterogeneity via tree-edit distance, Scientific Reports, vol. 12(1), art no 1960.

Centofanti, F., Fontana, M., Lepore, A., Vantini, S. (2022).
Smooth LASSO estimator for the Function-on-Function linear regression model, Computational Statistics and Data Analysis, art no 107556.

Centofanti, F., Lepore, A., Menafoglio, A., Palumbo, B., Vantini, S. (2022).
Adaptive smoothing spline estimator for the function-on-function linear regression model, Computational Statistics Cited 1 time.

Clarotto, L., Allard, D., Menafoglio, A. (2022).
A new class of α-transformations for the spatial analysis of Compositional Data, Spatial Statistics, art no 10057.

Colecchia, M., Paolini, B., Pini, G.M., Carpenito, L., Maghini, B., Avuzzi, B., et al (2022).
Total embedding of spermatic cord and hilar soft tissue in orchiectomy for seminoma: does the extensive sampling improve pathologic risk factors?, Virchows Archiv, vol. 481(5), pp. 695-70.

Didkovskyi, O., Ivanov, V., Radice, A., Papini, M., Longoni, L., Menafoglio, A. (2022).
A Comparison Between Machine Learning and Functional Geostatistics Approaches for Data-Driven Analyses of Sediment Transport in a Pre-Alpine Stream, Mathematical Geosciences, vol. 54(3), pp. 467-50.

Diquigiovanni, J., Fontana, M., Vantini, S. (2022).
Conformal prediction bands for multivariate functional data, Journal of Multivariate Analysis, art no 10487.

Elías, A., Jiménez, R., Paganoni, A.M., Sangalli, L.M. (2022).
Integrated Depths for Partially Observed Functional Data, Journal of Computational and Graphical Statistics Cited 4 times.

Fabris, E., Menzio, S., Gregorio, C., Pezzato, A., Stolfo, D., Aleksova, A., et al (2022).
Effect of prehospital treatment in STEMI patients undergoing primary PCI, Catheterization and Cardiovascular Interventions, vol. 99(5), pp. 1500-1508.

Falco, L., Fabris, E., Gregorio, C., Pezzato, A., Milo, M., Massa, L., et al (2022).
Early prognostic stratification and identification of irreversibly shocked patients despite primary percutaneous coronary intervention, Journal of Cardiovascular Medicine, vol. 23(4), pp. 247-25.

Ferraccioli, F., Sangalli, L.M., Finos, L. (2022).
Some first inferential tools for spatial regression with differential regularization, Journal of Multivariate Analysis, art no 10486.

Fiz, F., Masci, C., Costa, G., Sollini, M., Chiti, A., Ieva, F., et al (2022).
PET/CT-based radiomics of mass-forming intrahepatic cholangiocarcinoma improves prediction of pathology data and survival, European Journal of Nuclear Medicine and Molecular Imaging, vol. 49(10), pp. 3387-3400.

Franceschini, D., Polenghi, V., Franzese, C., Comito, T., Navarria, P., D’Agostino, G.R., et al (2022).
Oligoscore: a clinical score to predict overall survival in patients with oligometastatic disease treated with stereotactic body radiotherapy, Acta Oncologica, vol. 61(5), pp. 553-559.

Gregorio, C., Cappelletto, C., Romani, S., Stolfo, D., Merlo, M., Barbati, G. (2022).
Using marginal structural joint models to estimate the effect of a time-varying treatment on recurrent events and survival: An application on arrhythmogenic cardiomyopathy, Biometrical Journal, vol. 64(8), pp. 1374-138.

Hron, K., Menafoglio, A., Palarea-Albaladejo, J., Filzmoser, P., Talská, R., Egozcue, J.J. (2022).
Weighting of Parts in Compositional Data Analysis: Advances and Applications, Mathematical Geosciences, vol. 54(1), pp. 71-93.

Hron, K., Machalová, J., Menafoglio, A. (2022).
Bivariate densities in Bayes spaces: orthogonal decomposition and spline representation, Statistical Papers Cited 1 time.

Manca, P., Stolfo, D., Merlo, M., Gregorio, C., Cannatà, A., Ramani, F., et al (2022).
Transient versus persistent improved ejection fraction in non-ischaemic dilated cardiomyopathy, European Journal of Heart Failure, vol. 24(7), pp. 1171-1179.

Mascaretti, A., Dell’Agostino, L., Arena, M., Flori, A., Menafoglio, A., Vantini, S. (2022).
Heterogeneity of technological structures between EU countries: An application of complex systems methods to Input–Output Tables, Expert Systems with Applications, art no 11787.

Masci, C., Ieva, F., Paganoni, A.M. (2022).
SEMIPARAMETRIC MULTINOMIAL MIXED-EFFECTS MODELS: A UNIVERSITY STUDENTS PROFILING TOOL, Annals of Applied Statistics, vol. 16(3), pp. 1608-1632.

Massi, M.C., Gasperoni, F., Ieva, F., Paganoni, A.M. (2022).
Feature selection for imbalanced data with deep sparse autoencoders ensemble, Statistical Analysis and Data Mining, vol. 15(3), pp. 376-39.

Massi, M.C., Dominoni, L., Ieva, F., Fiorito, G. (2022).
A Deep Survival EWAS approach estimating risk profile based on pre-diagnostic DNA methylation: An application to breast cancer time to diagnosis, PLoS Computational Biology, vol. 18(9), art no e100995.

Nuzzi, V., Cannatà, A., Pellicori, P., Manca, P., Stolfo, D., Gregorio, C., et al (2022).
Diuretic dose trajectories in dilated cardiomyopathy: prognostic implications, Clinical Research in Cardiology.

Nuzzi, V., Cannatà, A., Pellicori, P., Manca, P., Stolfo, D., Gregorio, C., et al (2022).
Correction: Diuretic dose trajectories in dilated cardiomyopathy: prognostic implications (Clinical Research in Cardiology, (2022), 10.1007/s00392-022-02126-8), Clinical Research in Cardiology.

Nuzzi, V., Raafs, A., Manca, P., Henkens, M.T.H.M., Gregorio, C., Boscutti, A., et al (2022).
Left Atrial Reverse Remodeling in Dilated Cardiomyopathy, Journal of the American Society of Echocardiography.

Peli, R., Menafoglio, A., Cervino, M., Dovera, L., Secchi, P. (2022).
Physics-based Residual Kriging for dynamically evolving functional random fields, Stochastic Environmental Research and Risk Assessment, vol. 36(10), pp. 3063-308.

Ponti, L., Perotto, S., Sangalli, L.M. (2022).
A PDE-regularized smoothing method for space–time data over manifolds with application to medical data, International Journal for Numerical Methods in Biomedical Engineering, vol. 38(12), art no e365.

Scimone, R., Menafoglio, A., Sangalli, L.M., Secchi, P. (2022).
A look at the spatio-temporal mortality patterns in Italy during the COVID-19 pandemic through the lens of mortality densities, Spatial Statistics, art no 100541.

Scimone, R., Taormina, T., Colosimo, B.M., Grasso, M., Menafoglio, A., Secchi, P. (2022).
Statistical Modeling and Monitoring of Geometrical Deviations in Complex Shapes With Application to Additive Manufacturing, Technometrics, vol. 64(4), pp. 437-456.

Spreafico, M., Ieva, F., Fiocco, M. (2022).
Modelling time-varying covariates effect on survival via functional data analysis: application to the MRC BO06 trial in osteosarcoma, Statistical Methods and Applications.

Torti, A., Arena, M., Azzone, G., Secchi, P., Vantini, S. (2022).
Bridge closure in the road network of Lombardy: a spatio-temporal analysis of the socio-economic impacts, Statistical Methods and Applications, vol. 31(4), pp. 901-923.

Torti, A., Galvani, M., Menafoglio, A., Secchi, P., Vantini, S. (2022).
A general bi-clustering algorithm for object data with an application to the analysis of a Lombardy railway line, International Journal of Approximate Reasoning, pp. 161-177.

Římalová, V., Fišerová, E., Menafoglio, A., Pini, A. (2022).
Inference for spatial regression models with functional response using a permutational approach, Journal of Multivariate Analysis, art no 104893.

Boschi, T., Chiaromonte, F., Secchi, P., Bing, L. (2021).
Covariance-based low-dimensional registration for function-on-function regression, Stat, vol. 10(1).

Cappozzo, A., Greselin, F., Murphy, T.B. (2021).
Robust variable selection for model-based learning in presence of adulteration, Computational Statistics & Data Analysis, vol. 158.

Cappozzo, A., Escudero, L.A., Francesca, G., Agustin, M.I. (2021).
Parameter Choice, Stability and Validity for Robust Cluster Weighted Modeling, Stats, vol. 4(3).

Cappozzo, A., Duponchel, L., Greselin, F., Murphy, T.B. (2021).
Robust variable selection in the framework of classification with label noise and outliers: Applications to spectroscopic data in agri-food, Analytica Chimica Acta, vol. 1153.

Costa, G., Cavinato, L., Masci, C., Fiz, F., Sollini, M., Politi, L.S., et al. (2021).
Virtual Biopsy for Diagnosis of Chemotherapy-Associated Liver Injuries and Steatohepatitis: A Combined Radiomic and Clinical Model in Patients with Colorectal Liver Metastases, Cancers, vol. 13(12).

Denti, F., Cappozzo, A., Greselin, F. (2021).
A two-stage Bayesian semiparametric model for novelty detection with robust prior information, Statistics and Computing, vol. 31(4).

Ferraccioli, F., Arnone, E., Finos, L., Ramsay, J.O., Sangalli, L.M. (2021).
Nonparametric density estimation over complicated domains, Journal Of The Royal Statistical Society Series B Statistical Methodology, vol. 83(2).

Ferraccioli, F., Sangalli, L.M., Finos, L. (2021).
Some first inferential tools for spatial regression with differential regularization, Journal of Multivariate Analysis.

Fontana, L., Masci, C., Ieva, F., Paganoni, A.M. (2021).
Performing Learning Analytics via Generalised Mixed-Effects Trees, Data, vol. 6(7).

Franco, N.R., Massi, M.C., Ieva, F., Manzoni, A., Paganoni, A.M., Zunino, P., et al. (2021).
Development of a method for generating SNP interaction-aware polygenic risk scores for radiotherapy toxicity, Radiotherapy and Oncology, vol. 159.

Lovato, I., Pini, A., Stamm, A., Taquet, M., Vantini, S. (2021).
Multiscale null hypothesis testing for network-valued data: Analysis of brain networks of patients with autism, Journal Of The Royal Statistical Society Series C-applied Statistics, vol. 70(2).

Masci, C., Ieva, F., Agasisti, T., Paganoni, A.M. (2021).
Evaluating class and school effects on the joint student achievements in different subjects: a bivariate semiparametric model with random coefficients, Computational Statistics, vol. 1.

Massi, M.C., Gasperoni, F., Ieva, F., Paganoni, A.M. (2021).
Feature selection for imbalanced data with deep sparse autoencoders ensemble, Statistical Analysis and Data Mining, vol. 15.

Olsen, N.L., Pini, A., Vantini, S. (2021).
False discovery rate for functional data, Test, vol. 00.

Pellagatti, M., Masci, C., Ieva, F., Paganoni, A.M. (2021).
Generalized mixed-effects random forest: A flexible approach to predict university student dropout, Statistical Analysis and Data Mining, vol. 14(3).

Rancati, T., Massi, M., Franco, N., Avuzzi, B., Azria, D., Choudhury, A., et al. (2021).
PH-0656 Prediction of toxicity after prostate cancer RT: the value of a SNP-interaction polygenic risk score, Radiotherapy and Oncology, vol. 161.

Scalvini, S., Bernocchi, P., Villa, S., Paganoni, A.M., La Rovere, M.T., Frigerio, M., et al. (2021).
Treatment prescription, adherence, and persistence after the first hospitalization for heart failure: A population-based retrospective study on 100785 patients, International Journal Of Cardiology, vol. 330.

Scimone, R., Menafoglio, A., Sangalli, L.M., Secchi, P. (2021).
A look at the spatio-temporal mortality patterns in Italy during the COVID-19 pandemic through the lens of mortality densities, Spatial Statistics.

Scimone, R., Taormina, T., Colosimo, B.M., Grasso, M., Menafoglio, A., Secchi, P., et al. (2021).
Statistical Modeling and Monitoring of Geometrical Deviations in Complex Shapes With Application to Additive Manufacturing, Technometrics, vol. NA.

Sollini, M., Bartoli, F., Cavinato, L., Ieva, F., Ragni, A., Marciano, A., et al. (2021).
[18F]FMCH PET/CT biomarkers and similarity analysis to refine the definition of oligometastatic prostate cancer, Ejnmmi Research, vol. 11(1).

Spreafico, M., Ieva, F. (2021).
Dynamic monitoring of the effects of adherence to medication on survival in Heart Failure patients: a joint modelling approach exploiting time-varying covariates, Biometrical Journal, vol. 63(2).

Spreafico, M., Ieva, F., Arlati, F., Capello, F., Fatone, F., Fedeli, F., et al. (2021).
Novel longitudinal Multiple Overall Toxicity (MOTox) score to quantify adverse events experienced by patients during chemotherapy treatment: a retrospective analysis of the MRC BO06 trial in osteosarcoma, Bmj Open, vol. 11.

Spreafico, M., Ieva, F. (2021).
Functional modeling of recurrent events on time-to-event processes, Biometrical Journal, vol. 63(5).

Borgonovo, F., Ferrante, V., Grilli, G., Pascuzzo, R., Vantini, S., Guarino, M., et al. (2020).
A data-driven prediction method for an early warning of coccidiosis in intensive livestock systems: A preliminary study, Animals, vol. 10(4).

Calissano, A., Sturla, P., Pucci, P., Fedeli, V., Vantini, S. (2020).
Going Beyond the Euclidean Setting in the Statistical Analysis of Human Movement in Urban Landscape,, Journal Of Digital Landscape Architecture, vol. 5.

Calissano, A., Vantini, S., Arena, M. (2020).
Monitoring rare categories in sentiment and opinion analysis: a Milan mega event on Twitter platform, Statistical Methods & Applications, vol. 29(4).

Ceddia, G., Martino, L.N., Parodi, A., Secchi, P., Campaner, S., Masseroli, M., et al. (2020).
Association rule mining to identify transcription factor interactions in genomic regions, Bioinformatics, vol. 36(4).

Christian, C., Antonio, L., Menafoglio, A., Biagio, P., Vantini, S. (2020).
Control charts for monitoring ship operating conditions and CO2 emissions based on scalar-on-function regression, Applied Stochastic Models in Business and Industry, vol. 36.

Colecchia, M., Bertolotti, A., Paolini, B., Giunchi, F., Necchi, A., Paganoni, A.M., et al. (2020).
The Leydig cell tumor Scaled Score (LeSS) A method to distinguish benign from malignant cases, with additional correlation with MDM2 and CDK4 amplification, Histopathology.

Fabio, C., Antonio, L., Menafoglio, A., Biagio, P., Vantini, S. (2020).
Functional Regression Control Chart, Technometrics, vol. 00.

Fiz, F., Viganò, L., Gennaro, N., Costa, G., La Bella, L., Boichuk, A., et al. (2020).
Radiomics of Liver Metastases: A Systematic Review, Cancers, vol. 12(10).

Gasperoni, F., Ieva, F., Paganoni, A.M., Jackson, C.H., Sharples, L. (2020).
Non-parametric frailty Cox models for hierarchical time-to-event data, Biostatistics, vol. 21(3).

Gasperoni, F., Ieva, F., Paganoni, A.M., Jackson, C.H., Sharples, L. (2020).
Evaluating the effect of healthcare providers on the clinical path of heart failure patients through a semi-Markov, multi-state model, Bmc Health Services Research, vol. 20(1).

Gatti, F., Menafoglio, A., Togni, N., Bonaventura, L., Brambilla, D., Papini, M., et al. (2020).
A novel downscaling procedure for compositional data in the Aitchison geometry with application to soil texture data, Stochastic Environmental Research and Risk Assessment, vol. 00.

Guadagnini, L., Menafoglio, A., Sanchez-Vila, X., Guadagnini, A. (2020).
Probabilistic assessment of spatial heterogeneity of natural background concentrations in large-scale groundwater bodies through Functional Geostatistics, Science Of The Total Environment, vol. 740.

Ieva, F., Paganoni, A.M. (2020).
Component-wise outlier detection methods for robustifying multivariate functional samples, Statistical Papers, vol. 61(2).

Lovato, I., Pini, A., Stamm, A., Vantini, S. (2020).
Model-free two-sample test for network-valued data, Computational Statistics & Data Analysis, vol. 144.

Martina, S., Margarita, K., Cavinato, L., Francesca, R., Matteo, B., Ieva, F., et al. (2020).
Methodological framework for radiomics applications in Hodgkin’s lymphoma, European Journal Of Hybrid Imaging, vol. 4(1).

Martino, A., Guatteri, G., Paganoni, A.M. (2020).
Multivariate Hidden Markov Models for disease progression, Statistical Analysis and Data Mining, vol. 13(5).

Martino, A., Guatteri, G., Paganoni, A.M. (2020).
Hidden Markov Models for multivariate functional data, Statistics & Probability Letters, vol. 167.

Massi, M.C., Ieva, F., Lettieri, E. (2020).
Data mining application to healthcare fraud detection: a two-step unsupervised clustering method for outlier detection with administrative databases, Bmc Medical Informatics and Decision Making, vol. 20.

Massi, M.C., Francesca, G., Ieva, F., Paganoni, A.M., Zunino, P., Manzoni, A., et al. (2020).
A Deep Learning Approach Validates Genetic Risk Factors for Late Toxicity After Prostate Cancer Radiotherapy in a REQUITE Multi-National Cohort, Frontiers in Oncology, vol. 10.

Menafoglio, A., Sara, S., Giovanni, L., Francesca, P. (2020).
Simulation of seismic ground motion fields via object-oriented spatial statistics with an application in Northern Italy, Stochastic Environmental Research and Risk Assessment, vol. 34(10).

Pallonetto, F., Galvani, M., Torti, A., Vantini, S. (2020).
A framework for analysis and expansion of public charging infrastructure under fast penetration of electric vehicles, World Electric Vehicle Journal, vol. 11(1).

Paulon, G., De Iorio, M., Guglielmi, A., Ieva, F. (2020).
Joint modelling of recurrent events and survival: a Bayesian nonparametric approach, Biostatistics, vol. 21(1).

Rea, F., Ieva, F., Pastorino, U., Apolone, G., Barni, S., Merlino, L., et al. (2020).
Number of lung resections performed and long-term mortality rates of patients after lung cancer surgery: evidence from an Italian investigation, European Journal Of Cardio-thoracic Surgery, vol. 58(1).

Spreafico, M., Gasperoni, F., Barbati, G., Ieva, F., Scagnetto, A., Zanier, L., et al. (2020).
Adherence to Disease-Modifying Therapy in Patients Hospitalized for HF: Findings from a Community-Based Study, American Journal Of Cardiovascular Drugs, vol. 20.

Torti, A., Pini, A., Vantini, S. (2020).
Modelling time-varying mobility flows using function-on-function regression: Analysis of a bike sharing system in the city of Milan, Journal Of The Royal Statistical Society Series C-applied Statistics, vol. 70(1).

Arnone, E., Azzimonti, L., Nobile, F., Sangalli, L.M. (2019).
Modeling spatially dependent functional data via regression with differential regularization, Journal Of Multivariate Analysis, vol. 170.

Chiappa, A.S., Micheletti, S., Peli, R., Perotto, S. (2019).
Mesh adaptation-aided image segmentation, Communications in Nonlinear Science & Numerical Simulation, vol. 74.

Federico, R., Giuseppe, M., Massimo, M., Anna, C., Claudia, S., Luca, M., et al. (2019).
Adherence to recommendations and clinical outcomes of patients hospitalized for stroke: the role of the admission ward – a real-life investigation from Italy, Neurological Sciences, vol. 40(7).

Fontana, M., Tavoni, M., Vantini, S. (2019).
Functional Data Analysis of high-frequency load curves reveals drivers of residential electricity consumption, Plos One, vol. 14(6).

Mancini, L., Paganoni, A.M. (2019).
Marked point process models for the admissions of heart failure patients, Statistical Analysis and Data Mining, vol. 12(2).

Martino, A., Ghiglietti, A., Ieva, F., Paganoni, A.M. (2019).
A k-means procedure based on a Mahalanobis type distance for clustering multivariate functional data, Statistical Methods & Applications, vol. 28.

Masci, C., Paganoni, A.M., Ieva, F. (2019).
Semiparametric mixed-effects models for unsupervised classification of Italian schools, Journal Of The Royal Statistical Society. Series A. Statistics in Society, vol. 182(4).

Menafoglio, A., Secchi, P. (2019).
O2S2: A new venue for computational geostatistics, Applied Computing and Geosciences, vol. 2.

Pini, A., Spreafico, L., Vantini, S., Vietti, A. (2019).
Multi-aspect local inference for functional data: Analysis of ultrasound tongue profiles, Journal Of Multivariate Analysis, vol. 170.

Riva, P., Sturla, P., Calissano, A., Vantini, S. (2019).
Landscape Perception through Complex Data:Exploring George Hargreaves’s Queen Elizabeth Olympic Park in London, Journal Of Digital Landscape Architecture.

Scalvini, S., Grossetti, F., Paganoni, A.M., Teresa La Rovere, M., Pedretti, R.F., Frigerio, M., et al. (2019).
Impact of in-hospital cardiac rehabilitation on mortality and readmissions in heart failure: A population study in Lombardy, Italy, from 2005 to 2012, European Journal Of Preventive Cardiology, vol. 26(8).

Tantardini, M., Ieva, F., Tajoli, L., Piccardi, C. (2019).
Comparing methods for comparing networks, Scientific Reports, vol. 9(1).

Abramowicz, K.P., Häger, C.K., Pini, A., Schelin, L., Sjöstedt de Luna, S., Vantini, S., et al. (2018).
Nonparametric inference for functional-on-scalar linear models applied to knee kinematic hop data after injury of the anterior cruciate ligament, Scandinavian Journal Of Statistics, vol. 45(4).

Andrea, G., Maria Giovanna Scarale, , Rosalba, M., Ieva, F., Luigi, M., Cecilia, G., et al. (2018).
Urn models for response-adaptive randomized designs: a simulation study based on a nonadaptive randomized trial, Journal Of Biopharmaceutical Statistics, vol. 28(6).

Ballestrero, A., Bellan, R., Biedermann, B., Bittrich, C., Brivio, I., Cardini, A., et al. (2018).
Vector boson scattering: Recent experimental and theory developments, Reviews in Physics, vol. 3.

Bernardi, M.S., Carey, M., Ramsay, J.O., Sangalli, L.M. (2018).
Modeling spatial anisotropy via regression with partial differential regularization, Journal Of Multivariate Analysis, vol. 167.

Bottle, A., Ventura, C.M., Dharmarajan, K., Aylin, P., Ieva, F., Paganoni, A.M., et al. (2018).
Regional variation in hospitalisation and mortality in heart failure: comparison of England and Lombardy using multistate modelling, Health Care Management Science, vol. 21.

Cremona, M.A., Pini, A., Cumbo, F., Makova, K.D., Chiaromonte, F., Vantini, S., et al. (2018).
IWTomics: testing high-resolution sequence-based “Omics” data at multiple locations and scales, Bioinformatics, vol. X.

Dalla Costa, E., Pascuzzo, R., Leach, M.C., Dai, F., Lebelt, D., Vantini, S., et al. (2018).
Can grimace scales estimate the pain status in horses and mice? A statistical approach to identify a classifier, Plos One, vol. 13(8).

Ekin, T., Ieva, F., Ruggeri, F., Soyer, R. (2018).
Statistical Medical Fraud Assessment: Exposition to an Emerging Field, International Statistical Review, vol. 86(3).

Ferraro, S., Robbiano, C., Tosca, N., Panzeri, A., Paganoni, A.M., Panteghini, M., et al. (2018).
Serum human epididymis protein 4 vs. carbohydrate antigen 125 in ovarian cancer follow-up, Clinical Biochemistry, vol. 60.

Grossetti, F., Ieva, F., Paganoni, A.M. (2018).
A multi-state approach to patients affected by chronic heart failure, Health Care Management Science, vol. 21.

Guglielmi, A., Ieva, F., Paganoni, A.M., Quintana, F.A. (2018).
A semiparametric Bayesian joint model for multiple mixed-type outcomes: an application to acute myocardial infarction, Advances in Data Analysis and Classification, vol. 12(2).

Ieva, F., Bitonti, D. (2018).
Network analysis of comorbidity patterns in Heart Failure patients using administrative data., Epidemiology Biostatistics and Public Health, vol. 15(1).

Lo Mauro, A., Romei, M., Gandossini, S., Pascuzzo, R., Vantini, S., D’Angelo, M.G., et al. (2018).
Evolution of respiratory function in Duchenne muscular dystrophy from childhood to adulthood, European Respiratory Journal, vol. 51(2).

Masci, C., Johnes, G., Agasisti, T. (2018).
Student and school performance across countries: A machine learning approach, European Journal Of Operational Research, vol. 269(3).

Masci, C., De Witte, K., Agasisti, T. (2018).
The influence of school size, principal characteristics and school management practices on educational performance: An efficiency analysis of Italian students attending middle schools, Socio-economic Planning Sciences, vol. 61.

Menafoglio, A., Gaetani, G., Secchi, P. (2018).
Random domain decompositions for object-oriented Kriging over complex domains, Stochastic Environmental Research and Risk Assessment, vol. 32(12).

Menafoglio, A., Grasso, M.L.G., Secchi, P., Colosimo, B.M. (2018).
Profile Monitoring of Probability Density Functions via Simplicial Functional PCA with application to Image Data, Technometrics, vol. 60(4).

Ognjen, G., Menafoglio, A., Guang, Y., Jef, C. (2018).
Cokriging for multivariate Hilbert space valued random fields: application to multi-fidelity computer code emulation, Stochastic Environmental Research and Risk Assessment, vol. 32(7).

Pini, A., Stamm, A., Vantini, S. (2018).
Hotelling’s T2 in separable Hilbert spaces, Journal Of Multivariate Analysis, vol. 167.

Pini, A., Vantini, S., Colosimo, B.M., Grasso, M.L. (2018).
Domain-selective functional analysis of variance for supervised statistical profile monitoring of signal data, Journal Of The Royal Statistical Society Series C-applied Statistics, vol. 67(1).

Protti, M.P., Di Lullo, G., Marcatti, M., Heltai, S., Tresoldi, C., Paganoni, A.M., et al. (2018).
Immunomodulatory drugs in the context of autologous hematopoietic stem cell transplantation associate with reduced pro-tumor T cell subsets in multiple myeloma, Frontiers in Immunology, vol. 9.

Schiltz, F., Masci, C., Agasisti, T., Horn, D. (2018).
Using regression tree ensembles to model interaction effects: a graphical approach, Applied Economics, vol. 50(58).

Secchi, P. (2018).
On the role of statistics in the era of big data: A call for a debate, Statistics & Probability Letters, vol. 136.

Talská, R., Menafoglio, A., Machalová, J., Hron, K., Fišerová, E. (2018).
Compositional regression with functional response, Computational Statistics & Data Analysis, vol. 123.

Tarabelloni, N., Schenone, E., Collin, A., Ieva, F., Paganoni, A.M., Gerbeau, J.F., et al. (2018).
STATISTICAL ASSESSMENT AND CALIBRATION OF NUMERICAL ECG MODELS, Jp Journal Of Biostatistics, vol. 15(2).

Vantini, S. (2018).
Wishing the Non-parametric Re-evolution, Statistics & Probability Letters, vol. X.

Abramowicz, K., Arnqvist, P., Secchi, P., Luna, S.S., Vantini, S., Vitelli, V., et al. (2017).
Clustering misaligned dependent curves applied to varved lake sediment for climate reconstruction, Stochastic Environmental Research and Risk Assessment, vol. 31(1).

Agasisti, T., Ieva, F., Paganoni, A.M. (2017).
Heterogeneity, school-effects and the North/South achievement gap in Italian secondary education: evidence from a three-level mixed model, Statistical Methods & Applications, vol. 26(1).

Arnaboldi, M., Brambilla, M., Cassottana, B., Ciuccarelli, P., Vantini, S. (2017).
Urbanscope: A Lens to Observe Language Mix in Cities, American Behavioral Scientist, vol. 61(7).

Bernardi, M.S., Sangalli, L.M., Mazza, G., Ramsay, J.O. (2017).
A penalized regression model for spatial functional data with application to the analysis of the production of waste in Venice province, Stochastic Environmental Research and Risk Assessment, vol. 31(1).

Cabassi, A., Pigoli, D., Secchi, P., Carter, P.A. (2017).
Permutation tests for the equality of covariance operators of functional data with applications to evolutionary biology, Electronic Journal Of Statistics, vol. 11(2).

Ekin, T., Ieva, F., Ruggeri, F., Soyer, R. (2017).
On the Use of the Concentration Function in Medical Fraud Assessment., The American Statistician, vol. 71(3).

Frigerio, M., Mazzali, C., Paganoni, A.M., Ieva, F., Barbieri, P., Maistrello, M., et al. (2017).
Trends in heart failure hospitalizations, patient characteristics, in-hospital and 1-year mortality: A population study, from 2000 to 2012 in Lombardy, International Journal Of Cardiology, vol. 236.

Ghiglietti, A., Paganoni, A.M. (2017).
Exact tests for the means of Gaussian stochastic processes, Statistics & Probability Letters, vol. 131.

Ghiglietti, A., Ieva, F., Paganoni, A.M. (2017).
Statistical inference for stochastic processes: Two sample hypothesis tests, Journal Of Statistical Planning and Inference, vol. 180.

Ghiglietti, A., Ieva, F., Paganoni, A.M., Aletti, G. (2017).
On linear regression models in infinite dimensional spaces with scalar response, Statistical Papers, vol. 58(2).

Ieva, F., Paganoni, A.M., Teresa, P. (2017).
Dynamic clustering of hazard functions: an application to disease progression in chronic heart failure, Health Care Management Science, vol. 20.

Ieva, F., Rienzner, M. (2017).
Critical values improvement for the standard normal homogeneity test by combining Monte Carlo and regression approaches, Journal Of Applied Statistics, vol. 44.

Ieva, F., Jackson, C.H., Sharples, L.D. (2017).
Multi-state modelling of repeated hospitalisation and death in patients with heart failure: The use of large administrative databases in clinical epidemiology, Statistical Methods in Medical Research, vol. 26(3).

Masci, C., Ieva, F., Agasisti, T., Paganoni, A.M. (2017).
Bivariate multilevel models for the analysis of mathematics and reading pupils’ achievements, Journal Of Applied Statistics, vol. 44(7).

Menafoglio, A., Secchi, P. (2017).
Statistical analysis of complex and spatially dependent data: A review of Object Oriented Spatial Statistics, European Journal Of Operational Research, vol. 258(2).

Nicolai, N., Tarabelloni, N., Gasperoni, F., Catanzaro, M., Stagni, S., Torelli, T., et al. (2017).
Laparoscopic retroperitoneal lymph-node dissection (L-RPLND) in clinical stage I non-seminomatous germ-cell tumors of the testis (NSGCTT): safety and efficacy analyses in a high-volume center, The Journal Of Urology, vol. 1.

Paganoni, A.M., Sangalli, L.M. (2017).
Functional regression models: some directions of future research, Statistical Modelling, vol. 17(1-2).

Parodi, A.C.L., Sangalli, L.M., Vantini, S., Amati, B., Secchi, P., Morelli, M.J., et al. (2017).
FunChIP: an R/Bioconductor package for functional classification of ChIP-seq shapes, Bioinformatics, vol. 33(16).

Pini, A., Vantini, S. (2017).
Interval-wise testing for functional data, Journal Of Nonparametric Statistics, vol. 29(2).

Taroni, P., Paganoni, A.M., Ieva, F., Pifferi, A.G., Quarto, G., Abbate, F., et al. (2017).
Non-invasive optical estimate of tissue composition to differentiate malignant from benign breast lesions: A pilot study, Scientific Reports, vol. 7.