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Applied Statistics

Present position: Professor of Statistics at the Department of Economics and Law, University of Cassino and Southern Lazio.


Ph.D. 1998, Federico II University of Naples, IT
M.Sc. 1998, University of Minnesota, USA
Research interest: Graphical methods and data visualization. Model building and diagnostics in regression. Nonparametric multivariate analysis and data depth. Statistical process control.

Awards/Scientific Positions:

Memberships/Refereeing for Journals:


Main Publications:

Costantini P, Linting M, Porzio G.C. (2010). Mining performance data through nonlinear PCA with optimal scaling. Applied Stochastic Models in Business and Industry, 26, 85-101; doi: 10.1002/asmb.771

Porzio G.C., Ragozini G. (2009). On the stochastic ordering of folded binomials. Statistics and Probability Letters, 79, 1299-1304; doi: 10.1016/j.spl.2009.01.021.

Porzio G.C., Ragozini G., Vistocco D. (2008). On the use of archetypes as benchmarks. Applied Stochastic Models in Business and Industry, 24, 419-437.

Porzio G.C., Ragozini G. (2007), Multivariate Control Charts from a Data Mining Perspective, in: Recent Advances in Data Mining of Enterprise Data, Chapter 9, Liao, T.W. and E. Triantaphyllou (Eds.), World Scientific, Singapore, 413-462.

Porzio G.C., Vitale M.P. (2007) Exploring Nonlinearities in Path Models, Quality and Quantity, 41, 937-954.

Porzio G.C., Ragozini G. (2003) Visually Mining Off-line Data for Quality Improvement, Quality and Reliability Engineering International, 19, 273-283.

Porzio G.C. (2002) A Simulated Band to Check Binary Regression Models, Metron - International Journal of Statistics, LX, 1-2, 83-95.

Pan W., Connett J.E., Porzio G.C., Weisberg S. (2001) Graphical Model Checking with Correlated Response Data, Statistics in Medicine, 20, 2935-2949.

De Stefanis S., Porzio G.C. (1999) Dynamic Graphics and Model Validation: An Application to Best-Practice Production Functions, Applied Stochastic Models in Business and Industry, 15, 259-267.

Porzio G.C. (1997) Interpretation and Efficient Computation of the Andrews-Pregibon Statistic for Multiple Outliers in Multivariate Data, Statistica Applicata - Italian Journal of Applied Statistics, 9, 387-401.

[Ultima modifica: mercoledì 13 settembre 2017]