Full Professor of Statistics
Department of Economics and Business
University of Catania
Corso Italia, 55, 95128, Catania, Italy.
Tel: +(39) 0957537640
Email: antonio.punzo@unict.it
Web: http://www.dei.unict.it/antonio.punzo
ORCID: https://orcid.org/0000-0001-7742-1821
Curriculum Vitae: Download CV
Education
- 10/2015–10/2018 Associate Professor of Statistics, University of Catania, Department of Economics and Business.
- 11/2010–9/2015 Assistant Professor of Statistics, University of Catania, Department of Economics and Business.
- 2/2013–7/2013 Visiting Professor of Statistics, University of Guelph (Canada, Ontario), Department of Mathematics & Statistics (Director: Prof. Paul D. McNicholas).
- 6/2008–6/2010 Research Fellow of Statistics, University of Catania.
- 4/2008 Ph.D. in Methodological and Applied Statistics, University of Milano-Bicocca.
- 6/2004 Laurea (cum laude) in Statistical and Actuarial Sciences, University of Calabria.
Research Interests
Mixture Models, Hidden Markov Models, Model-Based Clustering, Heavy-tailed distributions, Serial Dependence, Item Response Theory, Nonparametric Techniques.
Current Teaching
- Professor of “An Introduction to Finite Mixture Models” (20 hours) for the Ph.D. in “Economics, Management and Statistics” (DOT1314289) of the University of Messina.
- Professor of “Statistical Models for Economics and Finance” (60 hours) for the Department of Economics and Business of the University of Catania.
- Professor of “Statistics” (60 hours) for the Department of Economics and Business of the University of Catania.
List of publications
2019
- Tomarchio S. D. and Punzo A. (2019). Modelling the loss given default distribution via a family of zero-and-one inflated mixture models. Journal of the Royal Statistical Society: Series A, (forthcoming).
- Ingrassia S. and Punzo A. (2019). Cluster validation for mixtures of regressions via the total sum of squares decomposition. Journal of Classification, (forthcoming).
- Mazza A. and Punzo A. (2019). Mixtures of multivariate contaminated normal regression models. Statistical Papers, (forthcoming).
- Zarei S., Mohammadpour A., Ingrassia S. and Punzo A. (2019). On the use of the sub-Gaussian α-stable distribution in the cluster-weighted model. Iranian Journal of Science and Technology, Transactions A: Science, (forthcoming).
- Punzo A. (2019). A new look at the inverse Gaussian distribution with applications to insurance and economic data. Journal of Applied Statistics, 46(7): 1260–1287.
- Maruotti A., Punzo A. and Bagnato L. (2018). Hidden Markov and semi-Markov models with multivariate leptokurtic-normal components for robust modeling of daily returns series. Journal of Financial Econometrics, 17(1): 91–117.
- Morris K., Punzo A., McNicholas P. D. and Browne R. P. (2019). Asymmetric Clusters and Outliers: Mixtures of Multivariate Contaminated Shifted Asymmetric Laplace Distributions. Computational Statistics & Data Analysis, 132: 145–166.
2018
- Mazza A., Punzo A. and Ingrassia S. (2018). flexCWM: A Flexible Framework for Cluster-Weighted Models. Journal of Statistical Software, 86(2), 1-30.
- Punzo A., Mazza A. and Maruotti A. (2018). Fitting insurance and economic data with outliers: A flexible approach based on finite mixtures of contaminated gamma distributions. Journal of Applied Statistics, 45(14), 2563–2584.
- Punzo A., Mazza A. and McNicholas P. D. (2018). ContaminatedMixt: An R Package for Fitting Parsimonious Mixtures of Multivariate Contaminated Normal Distributions. Journal of Statistical Software, 85(10), 1–25.
- Punzo A., Bagnato L. and Maruotti A. (2018). Compound unimodal distributions for insurance losses. Insurance: Mathematics and Economics, 81, 95–107.
- Bagnato L., De Capitani L. and Punzo A. (2018). Testing for serial independence: Beyond the Portmanteau approach. The American Statistician, 72(3), 219–238.
- Punzo A., Ingrassia S. and Maruotti A. (2018). Multivariate generalized hidden Markov regression models with random covariates: physical exercise in an elderly population. Statistics in Medicine, 37(19), 2797–2808.
2017
- Mazza A., Punzo A., and Ingrassia S. (2017). flexCWM: A Flexible Framework for Cluster-Weighted Models, Journal of Statistical Software, (forthcoming).
- Punzo A. and McNicholas P. D. (2017). Robust clustering in regression analysis via the contaminated Gaussian cluster-weighted model, Journal of Classification, 34(2), (forthcoming).
- Punzo A., Mazza A., and McNicholas P. D. (2017). ContaminatedMixt: An R Package for Fitting Parsimonious Mixtures of Multivariate Contaminated Normal Distributions, Journal of Statistical Software, (forthcoming).
- Bagnato L., De Capitani L. and Punzo A. (2017) Testing for serial independence: Beyond the Portmanteau approach, The American Statistician, (forthcoming).
- Maruotti A. and Punzo A. (2017). Model-based time-varying clustering of multivariate longitudinal data with covariates and outliers, Computational Statistics & Data Analysis, 113, 475–496.
- Mazza A. and Punzo A. (2017) Dealing with omitted answers in a survey on social integration of immigrants in Italy. Mathematical Population Studies, 24(2), 84–102.
- Dang U. J., Punzo A., McNicholas P. D., Ingrassia S. and Browne R. P. (2017). Multivariate response and parsimony for Gaussian cluster-weighted models, Journal of Classification, 34(1), 4–34.
- Bagnato L., Punzo A. and Zoia M. G. (2017). The multivariate leptokurtic-normal distribution and its application in model-based clustering, Canadian Journal of Statistics, 45(1), 95–119.
- Bagnato L., De Capitani L. and Punzo A. (2017). A diagram to detect serial dependencies: an application to transport time series, Quality & Quantity, 51(2), 581–594.
2016
- Berta P., Ingrassia S.,Punzo A. and Vittadini G. (2016). Cluster-weighted multilevel models for the evaluation of hospitals. Metron, 74(3), 275–292.
- Punzo A. and Maruotti A. (2016). Clustering multivariate longitudinal observations: The contaminated Gaussian hidden Markov model. Journal of Computational and Graphical Statistics, 25(4), 1097–1116.
- Punzo A. ;and McNicholas P. D. (2016). Parsimonious mixtures of multivariate contaminated normal distributions, Biometrical Journal, 58(6), 1506–1537.
- Bagnato L., De Capitani L. and ;Punzo A. (2016). The Kullback-Leibler autodependogram. Journal of Applied Statistics, 43(14), 2574–2594.
- Mazza A. and Punzo A. (2016). Spatial attraction in migrants' settlement patterns in the city of Catania. Demographic Research, 35(5), 117–138.
- Maruotti A., Punzo A., Mastrantonio G. and Lagona F. (2016). A time-dependent extension of the projected normal regression model for longitudinal circular data based on a hidden Markov heterogeneity structure, Stochastic Environmental Research and Risk Assessment , 30(6), 1725–1740.
- Punzo A. and Ingrassia S. (2016). Clustering bivariate mixed-type data via the cluster-weighted model. Computational Statistics, 31(3), 989–1013.
- Punzo A., Browne R. P. and McNicholas P. D. (2016). Hypothesis testing for mixture model selection. Journal of Statistical Computation and Simulation, 86(14): 2797–2818.
- Ingrassia S. and Punzo A. (2016). Decision boundaries for mixtures of regressions, Journal of the Korean Statistical Society, 45(2): 295–306.
2015
- Subedi S., Punzo A., Ingrassia S. and McNicholas P. D. (2015). Cluster-weighted t-factor analyzers for robust model-based clustering and dimension reduction, Statistical Methods & Applications, 24(4): 623–649.
- Ingrassia S., Punzo A., Vittadini G. and Minotti S. C. (2015). The generalized linear mixed cluster-weighted model, Journal of Classification, ;32(1): 85–113.
- Mazza A. and Punzo A. (2015). Bivariate discrete beta kernel graduation of mortality data, Lifetime Data Analysis, 21(3): 419–433.
- Bagnato L., De Capitani L., Mazza A. and Punzo A. (2015). SDD: An R package for serial dependence diagrams. Journal of Statistical Software, 64(Code Snippet 2): 1–19.
- Mazza A. and Punzo A. (2015). On the upward bias of the dissimilarity index and its corrections, Sociological Methods & Research, 44(1): 80–107.
2014
- Bagnato L., De Capitani L. andPunzo A. (2014). Testing serial independence via density-based measures of divergence, Methodology and Computing in Applied Probability, 16(3): 627–641.
- Mazza A., Punzo A. and McGuire B. (2014). KernSmoothIRT: An R package for kernel smoothing in Item Response Theory, Journal of Statistical Software, 58(6): 1–34.
- Punzo A. (2014) Flexible mixture modeling with the polynomial Gaussian cluster-weighted model, Statistical Modelling, 14(3): 257–291.
- Mazza A. and Punzo A. (2014). DBKGrad: An R package for mortality rates graduation by fixed and adaptive discrete beta kernel techniques, Journal of Statistical Software, 57(Code Snippet 2): 1–18.
- Bagnato L., De Capitani L. and Punzo A. (2014). Detecting serial dependencies with the reproducibility probability autodependogram, AStA Advances in Statistical Analysis, 98(1): 35–61.
- Bertoli-Barsotti L. and Punzo A. (2014). Refusal to answer specific questions in a survey: A case study, Communications in Statistics - Theory and Methods , 43(4): 826–838.
- Ingrassia S., Minotti S. C. and Punzo A. (2014). Model-based clustering via linear cluster-weighted models, Computational Statistics & Data Analysis, 71(4): 159–182.
- Bagnato L., Greselin F. and Punzo A. (2014). On the spectral decomposition in normal discriminant analysis, Communications in Statistics - Simulation and Computation, 43(6): 1471–1489.
2013
- Punzo A. and Ingrassia S. (2013). On the use of the generalized linear exponential cluster-weighted model to assess local linear independence in bivariate data, QdS - Journal of Methodological and Applied Statistics , 15: 131–144.
- Bertoli-Barsotti L. and ;Punzo A. (2013). Rasch analysis for binary data with nonignorable nonresponses, Psicológica , 34(1): 97–123.
- Subedi S., Punzo A., Ingrassia S. and McNicholas P. D. (2013). Clustering and classification via cluster-weighted factor analyzers, Advances in Data Analysis and Classification , ;7(1): 5–40.
- Bertoli-Barsotti L. and Punzo A. (2013). Modelling missingness with a Rasch-type model, Annales del'I.S.U.P. , 57(1–2): 29–44.
- Bagnato L. and Punzo A. (2013). Finite mixtures of unimodal beta and gamma densities and the k-bumps algorithm, Computational Statistics , 28(4): 1571–1597.
- Greselin F. and Punzo A. (2013). Closed likelihood ratio testing procedures to assess similarity of covariance matrices, The American Statistician, 67(3): 117–128.
2012
- Bagnato L., Punzo A. and Nicolis O. (2012). The Autodependogram: A Graphical Device to Investigate Serial Dependences, Journal of Time Series Analysis, 33(2): 233–254.
- Punzo A. and Zini A. (2012). Discrete Approximations of Continuous and Mixed Measures on a Compact Interval. Statistical Papers , 53(3): 563–575.
- Bertoli-Barsotti L. and Punzo A. (2012). Comparison of two bias reduction techniques for the Rasch model, Electronic Journal of Applied Statistical Analysis, 5(3): 360–366.
Before 2012
- Greselin F., Ingrassia S. and Punzo A. (2011). Assessing the pattern of covariance matrices via an augmentation multiple testing procedure, Statistical Methods & Applications, 20(2): 141–170.
- Bagnato L. and Punzo A. (2010). On the Use of χ2-Test to Check Serial Independence, VIII(1): 57–74.
- Punzo A. (2009). On Kernel Smoothing in Polytomous IRT: A New Minimum Distance Estimator, Quaderni di Statistica, 11: 15–37.
- Bagnato L. and Punzo A. (2009). Nonparametric Bootstrap Test for Autoregressive Additive Models, Statistics in Transition, 10(3), 359–370.
