Publications @Statistics


Agasisti, T., Cannistra, M., Soncin, M., Marazzina, D. (2022).
Financial Education during COVID-19 – Assessing the effectiveness of an online programme in a high school, Applied Economics.

Arnone, E., Kneip, A., Nobile, F., Sangalli, L.M. (2022).
Some first results on the consistency of spatial regression with partial differential equation regularization, Statistica Sinica, vol. 32.

Calissano, A., Feragen, A., Vantini, S. (2022).
Graph-valued regression: Prediction of unlabelled networks in a non-Euclidean graph space, Journal Of Multivariate Analysis, vol. 190.

Caramenti, L., Menafoglio, A., Sara, S., Giovanni, L. (2022).
Multi-source geographically weighted regression for regionalized ground-motion models, Spatial Statistics, vol. 47.

Clarotto, L., Denis, A., Menafoglio, A. (2022).
A new class of alpha-transformations for the spatial analysis of Compositional Data, Spatial Statistics, vol. 47.

Diquigiovanni, J., Fontana, M., Vantini, S. (2022).
Conformal prediction bands for multivariate functional data, Journal Of Multivariate Analysis, vol. 189.

Karel, H., Menafoglio, A., Javier, P.A., Peter, F., Renáta, T., Egozcue Rubi, J.J., et al. (2022).
Weighting of Parts in Compositional Data Analysis: Advances and Applications, Mathematical Geosciences, vol. 54.

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. -.

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 & Applications.

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, vol. 142.

Veronika, Ř., Eva, F., Menafoglio, A., AlessiaPini, (2022).
Inference for spatial regression models with functional response using a permutational approach, Journal Of Multivariate Analysis, vol. 189.


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).

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.

Cavinato, L., Cardinaux, A., Jamal, W., Kjelgaard, M., Sinha, P., Barbieri, R., et al. (2019).Assessment of the Autonomic Response to Sensory Stimulation in Autism Spectrum Disorder, Computing in Cardiology.

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.