Dr. Rosaria Lombardo

Associate Professor
Universita degli Studi della Campania Luigi Vanvitelli, Italy

Highest Degree
Ph.D. in Computational Statistics and Application from University of Naples Federico II, Italy

My URL
https://livedna.org/39.20047

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Area of Interest:

Bayesian Inference
Applied Statistics
Statistical Theory
Regression Analysis
Data Analysis

Selected Publications

  1. Mangoni, O., R. Lombardo, I. Camminatiello, F. Margiotta, A. Passarelli and M. Saggiomo, 2017. Phytoplankton community to assess the environmental status of the Adriatic Sea via non-linear partial least squares regression. Quality Quantity, 51: 799-812.
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  2. Cammnitiello, I., R. Lombardo and J.F. Durand, 2017. Robust partial least squares regression for the evaluation of justice court delay. Quality Quantity, 51: 813-827.
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  3. Lombardo, R., E.J. Beh and P.M. Kroonenberg, 2016. Modelling trends in ordered correspondence analysis using orthogonal polynomials. Psychometrika, 81: 325-349.
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  4. Lombardo, R. and E.J. Beh, 2016. Variants of correspondence analysis. R J., 8: 167-184.

  5. Lombardo, R. and E.J. Beh, 2016. The prediction index of aggregate data. J. Applied Stat., 43: 1998-2018.
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  6. Beh, E.J. and R. Lombardo, 2015. Confidence regions and approximate p-values for classical and non symmetric correspondence analysis. Commun. Stat. Theory Methods, 44: 95-114.
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  7. Lombardo, R., P. Amenta, M. Vivien and R. Sabatier, 2012. Sensory analysis via multi-block multivariate additive PLS splines. J. Applied Stat., 39: 731-743.
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  8. Lombardo, R., J.F. Durand and A.P. Leone, 2012. Multivariate additive PLS spline boosting in agro-chemistry studies. Curr. Anal. Chem., 8: 236-253.
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  9. Lombardo, R. and T. Ringrose, 2012. Bootstrap confidence regions in non-symmetrical correspondence analysis. Electron. J. Applied Stat. Anal., 5: 413-417.
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  10. Beh, E.J. and R. Lombardo, 2012. A genealogy of correspondence analysis. Aust. New Zealand J. Stat., 54: 137-168.
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  11. Lombardo, R., J.F. Durand and A. Faraj, 2011. Iterative design of experiments by non-linear PLS models. A case study: The reservoir simulator data to forecast oil production. J. Classification, 28: 113-125.
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  12. Lombardo, R., E.J. Beh and A. D'Ambra, 2011. Studying the dependence between ordinal-nominal categorical variables via orthogonal polynomials. J. Applied Stat., 38: 2119-2132.
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  13. Lombardo, R., 2011. Three-way association measure decompositions: The Delta index. J. Stat. Plann. Inference, 141: 1789-1799.
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  14. Lombardo, R., 2011. The analysis of sensory and chemical-physical variables via multivariate additive PLS splines. Food Quality Preference, 22: 714-724.
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  15. Lombardo, R. and E.D. Valle, 2011. Data mining and exploratory data analysis for the evaluation of job satisfaction. iBusiness J., 3: 372-382.

  16. Beh, E.J., R. Lombardo and B. Simonetti, 2011. A European perception of food using two methods of correspondence analysis. Food Quality Preference, 22: 226-231.
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  17. Lombardo, R. and J.J. Meulman, 2010. Multiple correspondence analysis via polynomial transformations of ordered categorical variables. J. Classification, 27: 191-210.
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  18. Lombardo, R. and I. Camminatiello, 2010. CATANOVA for two-way cross classified categorical data. Statistics: J. Theor. Applied Stat., 44: 57-71.
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  19. Lombardo, R. and E.J. Beh, 2010. Simple and multiple correspondence analysis using orthogonal polynomials. J. Applied Stat., 37: 2101-2116.

  20. Lombardo, R., J.F. Durand and R. De Veaux, 2009. Model building in multivariate additive partial least squares splines via the GCV criterion. J. Chemometrics, 23: 605-617.
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  21. Lombardo, R., E.J. Beh and L. D'Ambra, 2007. Non-symmetric correspondence analysis with ordinal variables using orthogonal polynomials. Comput. Stat. Data Analysis, 52: 566-577.
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  22. Lombardo, R. and J.F. Durand, 2005. Discriminant partial least-squares via Splines: An application to evaluate Patient satisfaction. Stat. Applic., 3: 77-85.

  23. Lombardo, R., P. Kroonenberg and L. D’Ambra, 2000. Non-symmetric correspondence analysis and biplot representation: Comparing differences in market share distribution. Stat. Methods Applic., 9: 107-126.
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  24. D'Ambra, L., R. Lombardo and P. Amenta, 2000. Multivariate co-inertia analysis for qualitative data by partial least squares. Stat. Methods Applic., 9: 23-37.
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  25. Kroonenberg, P.M. and R. Lombardo, 1999. Nonsymmetric correspondence analysis: A tool for analysing contingency tables with a dependence structure. Multivariate Behav. Res., 34: 367-396.
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  26. Kroonenberg, P.M. and R. Lombardo, 1998. Nonsymmetric correspondence analysis: A tutorial. Kwantitatieve Methoden, 19: 57-83.
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  27. Lombardo, R. and L. D'Ambra, 1997. Internal and external decompositions for three-way contingency tables. Metron, 55: 171-184.

  28. Lombardo, R., A. Carlier and L. D'Ambra, 1996. Non-symmetric correspondence analysis for three-way contingency tables. Methodologica, 4: 59-80.
Member since September, 2017