International Journal of Statistics and Applications

International Journal of Statistics and Applications is a fully refereed international journal, which publishes original research papers and survey articles in all areas of statistics and applications. It is a broad based journal covering all branches of statistical sciences and their applications in medical, agricultural, econometric, physical or social sciences and industry, commerce and government and other scientific disciplines.

Rosaria Lombardo

Editor-in-Chief of International Journal of Statistics and Applications

Associate Professor, Second University of Naples, Italy

Research Areas

Data Mining and Regression Tools.Evaluation of Efficiency, Efficacy, Customer and Job Satisfaction. Statistical Quality Control. Sensorial and Chemical Data Analysis Linear and Non-linear Exploratory Data Analysis

Education

1994Ph.DComputational Statistics and Data Analysis

Experience

2010Director and Professor of the Master Course in “Programming, organization and management in health care services”, Economics Faculty & Faculty of Medicine-Second University of Naples
2001Associate professor in Statistics

Membership

Member of the Italian Statistical Society (SIS)
Member of the International Association of Statistical Computing, (IASC)
Member of the Italian Inter-university Research center for the evaluation of public services (C.R.I.S.P.)
Member of the Board of Directory of the International Association of Statistical Computing-European Regional Section (IASC-ERS)

Publications: Journals

[1]  Lombardo R, Amenta P, Vivien M, Sabatier R (2011) Sensory Analysis via Multi-block Multivariate Additive PLS Splines. Journal of Applied Statistics doi:10.1080/02664763.2011.611239.
[2]  Lombardo R (2011) The Analysis of Sensory and Chemical-Physical Variables via Multivariate Additive PLS Splines. Journal of Food and Quality Preference, 22:714-724, doi:10.1016/j.foodqual.2011.06.002.
[3]  Lombardo, R., Durand J. F. and Faraj, A. (2011), Iterative design of experiments by non-linear PLS models. A case study: the reservoir simulator data to forecast oil production, Journal of Classification (in press, DOI: 10.1007/s00357-011) vol. 28, n1, pag 113-125.
[4]  Lombardo R., Beh, E. J. and D'Ambra, A., (2011) Studying the dependence between ordinal-nominal categorical variables via orthogonal polynomials, Journal of Applied Statistics, 38, 2119-2132, DOI: 10.1080/02664763.2010.545118.
[5]  Lombardo, R., (2011), Three-way association measure decompositions: the Delta index, Journal of Statistical Planning and Inference, 141, 1789-1799.
[6]  Beh, E. J., Lombardo R. and Simonetti B., (2011), A European perception of food using two methods of correspondence analysis, Journal of Food and Quality Preference, 22, 226-231.
[7]  Lombardo, R. and Beh, E. J., (2010) Simple and multiple correspondence analysis using orthogonal polynomials, Journal of Applied Statistics, 37, 2101-2116.
[8]  Lombardo R. and Camminatiello, I., (2010) CATANOVA for two-way cross classified categorical data. Statistics: A Journal of Theoretical and Applied Statistics, 44, 57-71.
[9]  Lombardo, R. and Meulman, J. (2010), Multiple correspondence analysis via polynomial transformations of ordered categorical variables, Journal of Classification, 27, 191-216.
[10]  Lombardo, R., Tessitore, G. and van Rijckevorsel, J. L. A. (2009), Adaptive non-linear principal component and surface analysis, Journal of Advances and Applications in Statistics, 12, 85-98.
[11]  Lombardo, R., Durand, J. F. and De Veaux, R. (2009), Model building in multivariate additive partial least squares splines via the GCV criterion, Journal of Chemometrics, 23, 605-617.
[12]  Lombardo, R., Beh, E. J. and D'Ambra, L., (2007) Non-symmetric correspondence analysis with ordinal variables using orthogonal polynomials, Computational Statistics & Data Analysis, 52, 566-578.
[13]  Lombardo, R. and Durand, J. F. (2005), Discriminant partial least-squares via splines: An application to evaluate patient satisfaction, Statistica & Applicazioni, 3, 77-85.
[14]  D'Ambra, L., Lombardo, R. and Amenta, P. (2000), Multivariate co-inertia analysis for qualitative data by partial least squares, Journal of the Italian Statistical Society, 9, 23-37.
[15]  Lombardo, R., Kroonenberg, P. and D'Ambra, L. (2000), Non-symmetric correspondence analysis: a simple tool in market share distribution, Journal of the Italian Statistical Society, 9, 107-126.
[16]  Kroonenberg, P. and Lombardo, R. (1999), Non-symmetric correspondence analysis: A tool for analysing contingency tables with a dependence structure, Multivariate Behavioral Research, 34, 367-396.
[17]  Kroonenberg, P. and Lombardo, R. (1998), Non-symmetric correspondence analysis: A tutorial, Kwantitatieve Methoden, 58, 57-83.
[18]  Lombardo, R. and D'Ambra L. (1997), Internal and external decompositions for three-way contingency tables, Metron, 55, 171-184.
[19]  Lombardo, R., Carlier, A. and D'Ambra, L. (1996), Non-symmetric correspondence analysis for three-way contingency tables, Methodologica, 4, 59-80.