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Alessandro Barbiero

Personal Details

First Name:Alessandro
Middle Name:
Last Name:Barbiero
Suffix:
RePEc Short-ID:pba635
[This author has chosen not to make the email address public]
https://www.unimi.it/en/ugov/person/alessandro-barbiero

Affiliation

Dipartimento di Economia, Management e Metodi Quantitativi (DEMM)
Università degli Studi di Milano

Milano, Italy
http://www.demm.unimi.it/
RePEc:edi:damilit (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Nadia SOLARO & Alessandro BARBIERO & Giancarlo MANZI & Pier Alda FERRARI, 2015. "A Comprehensive Simulation Study on the Forward Imputation," Departmental Working Papers 2015-04, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
  2. Pier Alda FERRARI & Alessandro BARBIERO, 2011. "Generating ordinal data," Departmental Working Papers 2011-38, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
  3. Pier Alda FERRARI & Alessandro BARBIERO, 2011. "Generating ordinal data," Departmental Working Papers 2011-038, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.

Articles

  1. Alessandro Barbiero, 2024. "Correction to: Discrete analogues of continuous bivariate probability distributions," Annals of Operations Research, Springer, vol. 332(1), pages 1-1, January.
  2. Alessandro Barbiero, 2024. "Estimation of the reliability parameter for a Poisson-exponential stress-strength model," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(3), pages 1261-1272, March.
  3. Alessandro Barbiero & Asmerilda Hitaj, 2023. "Discrete approximations of continuous probability distributions obtained by minimizing Cramér-von Mises-type distances," Statistical Papers, Springer, vol. 64(5), pages 1669-1697, October.
  4. Alessandro Barbiero, 2022. "Properties and estimation of a bivariate geometric model with locally constant failure rates," Annals of Operations Research, Springer, vol. 312(1), pages 3-22, May.
  5. Alessandro Barbiero, 2022. "Discrete analogues of continuous bivariate probability distributions," Annals of Operations Research, Springer, vol. 312(1), pages 23-43, May.
  6. Alessandro Barbiero & Asmerilda Hitaj, 2022. "Approximation of continuous random variables for the evaluation of the reliability parameter of complex stress–strength models," Annals of Operations Research, Springer, vol. 315(2), pages 1573-1598, August.
  7. Alessandro Barbiero, 2021. "Inducing a desired value of correlation between two point-scale variables: a two-step procedure using copulas," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(2), pages 307-334, June.
  8. Alessandro Barbiero & Asmerilda Hitaj, 2020. "Goodman and Kruskal’s Gamma Coefficient for Ordinalized Bivariate Normal Distributions," Psychometrika, Springer;The Psychometric Society, vol. 85(4), pages 905-925, December.
  9. Alessandro Barbiero, 2019. "A bivariate geometric distribution allowing for positive or negative correlation," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(11), pages 2842-2861, June.
  10. Barbiero, A., 2019. "A bivariate count model with discrete Weibull margins," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 156(C), pages 91-109.
  11. Nadia Solaro & Alessandro Barbiero & Giancarlo Manzi & Pier Alda Ferrari, 2017. "A sequential distance-based approach for imputing missing data: Forward Imputation," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(2), pages 395-414, June.
  12. Alessandro Barbiero & Pier Alda Ferrari, 2015. "Simulation of correlated Poisson variables," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 31(5), pages 669-680, September.
  13. Alessandro Barbiero, 2013. "Parameter Estimation for Type III Discrete Weibull Distribution: A Comparative Study," Journal of Probability and Statistics, Hindawi, vol. 2013, pages 1-10, September.
  14. Barbiero, Alessandro, 2012. "A general discretization procedure for reliability computation in complex stress–strength models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(9), pages 1667-1676.
  15. Alessandro Barbiero, 2012. "Interval estimators for reliability: the bivariate normal case," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(3), pages 501-512, June.
  16. Ferrari, Pier Alda & Annoni, Paola & Barbiero, Alessandro & Manzi, Giancarlo, 2011. "An imputation method for categorical variables with application to nonlinear principal component analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2410-2420, July.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Nadia SOLARO & Alessandro BARBIERO & Giancarlo MANZI & Pier Alda FERRARI, 2015. "A Comprehensive Simulation Study on the Forward Imputation," Departmental Working Papers 2015-04, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.

    Cited by:

    1. Nadia Solaro & Alessandro Barbiero & Giancarlo Manzi & Pier Alda Ferrari, 2017. "A sequential distance-based approach for imputing missing data: Forward Imputation," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(2), pages 395-414, June.

Articles

  1. Alessandro Barbiero, 2022. "Properties and estimation of a bivariate geometric model with locally constant failure rates," Annals of Operations Research, Springer, vol. 312(1), pages 3-22, May.

    Cited by:

    1. Shaomin Wu & Hongyan Dui & Linmin Hu, 2024. "Construction of copulas for bivariate failure rates," Annals of Operations Research, Springer, vol. 341(2), pages 1177-1189, October.

  2. Alessandro Barbiero, 2022. "Discrete analogues of continuous bivariate probability distributions," Annals of Operations Research, Springer, vol. 312(1), pages 23-43, May.

    Cited by:

    1. Shaomin Wu & Hongyan Dui & Linmin Hu, 2024. "Construction of copulas for bivariate failure rates," Annals of Operations Research, Springer, vol. 341(2), pages 1177-1189, October.

  3. Alessandro Barbiero & Asmerilda Hitaj, 2020. "Goodman and Kruskal’s Gamma Coefficient for Ordinalized Bivariate Normal Distributions," Psychometrika, Springer;The Psychometric Society, vol. 85(4), pages 905-925, December.

    Cited by:

    1. Joanna Belle Bawar & Antonio Yango & Pedrito Jose Bermudo, 2023. "Work-Related Stress, Adversity Quotient, and Psychological Well-Being of Local College Instructors in the New Normal," Technium Social Sciences Journal, Technium Science, vol. 44(1), pages 592-616, June.

  4. Alessandro Barbiero, 2019. "A bivariate geometric distribution allowing for positive or negative correlation," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(11), pages 2842-2861, June.

    Cited by:

    1. M. C. Jones, 2024. "On Integral Representations Involving the Probability Generating Function for Inverse Moments of Positive Discrete Random Variables," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 86(2), pages 992-998, August.

  5. Barbiero, A., 2019. "A bivariate count model with discrete Weibull margins," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 156(C), pages 91-109.

    Cited by:

    1. Abdulhamid A. Alzaid & Weaam M. Alhadlaq, 2023. "A New Family of Archimedean Copulas: The Half-Logistic Family of Copulas," Mathematics, MDPI, vol. 12(1), pages 1-18, December.

  6. Nadia Solaro & Alessandro Barbiero & Giancarlo Manzi & Pier Alda Ferrari, 2017. "A sequential distance-based approach for imputing missing data: Forward Imputation," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(2), pages 395-414, June.

    Cited by:

    1. Emanuela Raffinetti & Pier Alda Ferrari, 2021. "A dependence measure flow tree through Monte Carlo simulations," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(2), pages 467-496, April.
    2. Atieno, Prisca, 2021. "The effects of outdated data and outliers on Kenya's 2019 Global Food Security Index score and rank," Research Theses 334773, Collaborative Masters Program in Agricultural and Applied Economics.

  7. Alessandro Barbiero & Pier Alda Ferrari, 2015. "Simulation of correlated Poisson variables," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 31(5), pages 669-680, September.

    Cited by:

    1. Mohamed A. Ayadi & Hatem Ben-Ameur & Nabil Channouf & Quang Khoi Tran, 2019. "NORTA for portfolio credit risk," Annals of Operations Research, Springer, vol. 281(1), pages 99-119, October.

  8. Alessandro Barbiero, 2013. "Parameter Estimation for Type III Discrete Weibull Distribution: A Comparative Study," Journal of Probability and Statistics, Hindawi, vol. 2013, pages 1-10, September.

    Cited by:

    1. Riccardo Patriarca & Tianya Hu & Francesco Costantino & Giulio Di Gravio & Massimo Tronci, 2019. "A System-Approach for Recoverable Spare Parts Management Using the Discrete Weibull Distribution," Sustainability, MDPI, vol. 11(19), pages 1-15, September.

  9. Barbiero, Alessandro, 2012. "A general discretization procedure for reliability computation in complex stress–strength models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(9), pages 1667-1676.

    Cited by:

    1. Alessandro Barbiero & Asmerilda Hitaj, 2022. "Approximation of continuous random variables for the evaluation of the reliability parameter of complex stress–strength models," Annals of Operations Research, Springer, vol. 315(2), pages 1573-1598, August.
    2. Yo Sheena, 2019. "Estimation of a continuous distribution on the real line by discretization methods," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(3), pages 339-360, April.
    3. Lujano-Rojas, J.M. & Osório, G.J. & Matias, J.C.O. & Catalão, J.P.S., 2016. "A heuristic methodology to economic dispatch problem incorporating renewable power forecasting error and system reliability," Renewable Energy, Elsevier, vol. 87(P1), pages 731-743.

  10. Alessandro Barbiero, 2012. "Interval estimators for reliability: the bivariate normal case," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(3), pages 501-512, June.

    Cited by:

    1. Nabakumar Jana & Somesh Kumar & Kashinath Chatterjee, 2016. "Bayes estimation for exponential distributions with common location parameter and applications to multi-state reliability models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(15), pages 2697-2712, November.
    2. Joby K. Jose & M. Drisya, 2020. "Time-dependent stress–strength reliability models based on phase type distribution," Computational Statistics, Springer, vol. 35(3), pages 1345-1371, September.

  11. Ferrari, Pier Alda & Annoni, Paola & Barbiero, Alessandro & Manzi, Giancarlo, 2011. "An imputation method for categorical variables with application to nonlinear principal component analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2410-2420, July.

    Cited by:

    1. Nadia Solaro & Alessandro Barbiero & Giancarlo Manzi & Pier Alda Ferrari, 2017. "A sequential distance-based approach for imputing missing data: Forward Imputation," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(2), pages 395-414, June.
    2. Arboretti, Rosa & Bonnini, Stefano & Corain, Livio & Salmaso, Luigi, 2014. "A permutation approach for ranking of multivariate populations," Journal of Multivariate Analysis, Elsevier, vol. 132(C), pages 39-57.
    3. Pier Alda FERRARI & Alessandro BARBIERO, 2011. "Generating ordinal data," Departmental Working Papers 2011-38, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.

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