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Francesca Greselin

Personal Details

First Name:Francesca
Middle Name:
Last Name:Greselin
Suffix:
RePEc Short-ID:pgr226

Affiliation

Dipartimento di Metodi Quantitativi per le Scienze Economiche e Aziendali
Scuola di Economia e Statistica
Università degli Studi di Milano-Bicocca

Milano, Italy
http://www.dimequant.unimib.it/
RePEc:edi:dqmibit (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2020. "The Social Welfare Implications of the Zenga Index," Papers 2006.12623, arXiv.org.
  2. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2017. "Lorenz versus Zenga Inequality Curves: a New Approach to Measuring Tax Redistribution and Progressivity," Working papers 046, Department of Economics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.
  3. Greselin, Francesca & Zitikis, Ricardas, 2015. "Measuring economic inequality and risk: a unifying approach based on personal gambles, societal preferences and references," MPRA Paper 65892, University Library of Munich, Germany.
  4. Greselin, Francesca & Pasquazzi, Leo, 2011. "Estimation of Zenga's new index of economic inequality in heavy tailed populations," MPRA Paper 31230, University Library of Munich, Germany.
  5. Greselin, Francesca & Pasquazzi, Leo & Zitikis, Ricardas, 2009. "Zenga’s new index of economic inequality, its estimation, and an analysis of incomes in Italy," MPRA Paper 17147, University Library of Munich, Germany.

Articles

  1. Andrea Cappozzo & Luis Angel García Escudero & Francesca Greselin & Agustín Mayo-Iscar, 2021. "Parameter Choice, Stability and Validity for Robust Cluster Weighted Modeling," Stats, MDPI, vol. 4(3), pages 1-14, July.
  2. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2021. "The Zenga Equality Curve: A New Approach to Measuring Tax Redistribution and Progressivity," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(4), pages 950-976, December.
  3. Cappozzo, Andrea & Greselin, Francesca & Murphy, Thomas Brendan, 2021. "Robust variable selection for model-based learning in presence of adulteration," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).
  4. Youri Davydov & Francesca Greselin, 2020. "Comparisons Between Poorest and Richest to Measure Inequality," Sociological Methods & Research, , vol. 49(2), pages 526-561, May.
  5. Francesca Greselin & Alina Jȩdrzejczak, 2020. "Analyzing the Gender Gap in Poland and Italy, and by Regions," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 26(4), pages 433-447, November.
  6. Andrea Cappozzo & Francesca Greselin & Thomas Brendan Murphy, 2020. "A robust approach to model-based classification based on trimming and constraints," 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. 14(2), pages 327-354, June.
  7. Francesca Greselin & Fabio Piacenza & Ričardas Zitikis, 2019. "Practice Oriented and Monte Carlo Based Estimation of the Value-at-Risk for Operational Risk Measurement," Risks, MDPI, vol. 7(2), pages 1-20, May.
  8. Youri Davydov & Francesca Greselin, 2019. "Inferential results for a new measure of inequality," The Econometrics Journal, Royal Economic Society, vol. 22(2), pages 153-172.
  9. Luis Angel García-Escudero & Alfonso Gordaliza & Francesca Greselin & Salvatore Ingrassia & Agustín Mayo-Iscar, 2018. "Eigenvalues and constraints in mixture modeling: geometric and computational issues," 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. 12(2), pages 203-233, June.
  10. Francesca Greselin & Ričardas Zitikis, 2018. "From the Classical Gini Index of Income Inequality to a New Zenga-Type Relative Measure of Risk: A Modeller’s Perspective," Econometrics, MDPI, vol. 6(1), pages 1-20, January.
  11. García-Escudero, Luis Angel & Gordaliza, Alfonso & Greselin, Francesca & Ingrassia, Salvatore & Mayo-Iscar, Agustín, 2016. "The joint role of trimming and constraints in robust estimation for mixtures of Gaussian factor analyzers," Computational Statistics & Data Analysis, Elsevier, vol. 99(C), pages 131-147.
  12. Greselin Francesca, 2014. "More Equal and Poorer, or Richer but More Unequal?," Stochastics and Quality Control, De Gruyter, vol. 29(2), pages 99-117, December.
  13. Francesca Greselin & Leo Pasquazzi & Ričardas Zitikis, 2013. "Contrasting the Gini and Zenga indices of economic inequality," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(2), pages 282-297, February.
  14. Francesca Greselin & Antonio Punzo, 2013. "Closed Likelihood Ratio Testing Procedures to Assess Similarity of Covariance Matrices," The American Statistician, Taylor & Francis Journals, vol. 67(3), pages 117-128, August.
  15. Francesca Greselin & Salvatore Ingrassia & Antonio Punzo, 2011. "Assessing the pattern of covariance matrices via an augmentation multiple testing procedure," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(2), pages 141-170, June.
  16. Francesca Greselin & Leo Pasquazzi & Ričardas Zitikis, 2010. "Zenga's New Index of Economic Inequality, Its Estimation, and an Analysis of Incomes in Italy," Journal of Probability and Statistics, Hindawi, vol. 2010, pages 1-26, April.

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. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2020. "The Social Welfare Implications of the Zenga Index," Papers 2006.12623, arXiv.org.

    Cited by:

    1. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2021. "The Zenga Equality Curve: A New Approach to Measuring Tax Redistribution and Progressivity," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(4), pages 950-976, December.

  2. Greselin, Francesca & Zitikis, Ricardas, 2015. "Measuring economic inequality and risk: a unifying approach based on personal gambles, societal preferences and references," MPRA Paper 65892, University Library of Munich, Germany.

    Cited by:

    1. Sebastian Fuchs & Ruben Schlotter & Klaus D. Schmidt, 2017. "A Review and Some Complements on Quantile Risk Measures and Their Domain," Risks, MDPI, vol. 5(4), pages 1-16, November.

  3. Greselin, Francesca & Pasquazzi, Leo & Zitikis, Ricardas, 2009. "Zenga’s new index of economic inequality, its estimation, and an analysis of incomes in Italy," MPRA Paper 17147, University Library of Munich, Germany.

    Cited by:

    1. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2021. "The Zenga Equality Curve: A New Approach to Measuring Tax Redistribution and Progressivity," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(4), pages 950-976, December.
    2. Matti Langel & Yves Tillé, 2012. "Inference by linearization for Zenga’s new inequality index: a comparison with the Gini index," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(8), pages 1093-1110, November.
    3. Greselin Francesca, 2014. "More Equal and Poorer, or Richer but More Unequal?," Stochastics and Quality Control, De Gruyter, vol. 29(2), pages 99-117, December.
    4. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2017. "Lorenz versus Zenga Inequality Curves: a New Approach to Measuring Tax Redistribution and Progressivity," Working papers 046, Department of Economics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.
    5. Pasquazzi Leo & Zenga Michele, 2018. "Components of Gini, Bonferroni, and Zenga Inequality Indexes for EU Income Data," Journal of Official Statistics, Sciendo, vol. 34(1), pages 149-180, March.
    6. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2020. "The Social Welfare Implications of the Zenga Index," Papers 2006.12623, arXiv.org.
    7. Youri Davydov & Francesca Greselin, 2020. "Comparisons Between Poorest and Richest to Measure Inequality," Sociological Methods & Research, , vol. 49(2), pages 526-561, May.
    8. Michele Zenga, 2016. "On the decomposition by subpopulations of the point and synthetic Zenga (2007) inequality indexes," METRON, Springer;Sapienza Università di Roma, vol. 74(3), pages 375-405, December.

Articles

  1. Andrea Cappozzo & Francesca Greselin & Thomas Brendan Murphy, 2020. "A robust approach to model-based classification based on trimming and constraints," 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. 14(2), pages 327-354, June.

    Cited by:

    1. Cappozzo, Andrea & Greselin, Francesca & Murphy, Thomas Brendan, 2021. "Robust variable selection for model-based learning in presence of adulteration," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).

  2. Francesca Greselin & Fabio Piacenza & Ričardas Zitikis, 2019. "Practice Oriented and Monte Carlo Based Estimation of the Value-at-Risk for Operational Risk Measurement," Risks, MDPI, vol. 7(2), pages 1-20, May.

    Cited by:

    1. Teodora Maria SUCIU (AVRAM), 2020. "Possibilities Of Evaluation Of The Expenditure Of The Clothing Industry By The Monte Carlo Method," Contemporary Economy Journal, Constantin Brancoveanu University, vol. 5(3), pages 29-37.
    2. Jiandong Ren & Kristina Sendova & Ričardas Zitikis, 2019. "Special Issue “Risk, Ruin and Survival: Decision Making in Insurance and Finance”," Risks, MDPI, vol. 7(3), pages 1-7, September.

  3. Youri Davydov & Francesca Greselin, 2019. "Inferential results for a new measure of inequality," The Econometrics Journal, Royal Economic Society, vol. 22(2), pages 153-172.

    Cited by:

    1. Mario Schlemmer, 2021. "Coupling the Gini and Angles to Evaluate Economic Dispersion," Papers 2110.13847, arXiv.org, revised Sep 2022.

  4. Luis Angel García-Escudero & Alfonso Gordaliza & Francesca Greselin & Salvatore Ingrassia & Agustín Mayo-Iscar, 2018. "Eigenvalues and constraints in mixture modeling: geometric and computational issues," 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. 12(2), pages 203-233, June.

    Cited by:

    1. Keefe Murphy & Thomas Brendan Murphy, 2020. "Gaussian parsimonious clustering models with covariates and a noise component," 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. 14(2), pages 293-325, June.
    2. Andrea Cappozzo & Francesca Greselin & Thomas Brendan Murphy, 2020. "A robust approach to model-based classification based on trimming and constraints," 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. 14(2), pages 327-354, June.
    3. Cong, Lin & Yao, Weixin, 2021. "A Likelihood Ratio Test of a Homoscedastic Multivariate Normal Mixture Against a Heteroscedastic Multivariate Normal Mixture," Econometrics and Statistics, Elsevier, vol. 18(C), pages 79-88.

  5. Francesca Greselin & Ričardas Zitikis, 2018. "From the Classical Gini Index of Income Inequality to a New Zenga-Type Relative Measure of Risk: A Modeller’s Perspective," Econometrics, MDPI, vol. 6(1), pages 1-20, January.

    Cited by:

    1. Luigi Mastronardi & Aurora Cavallo, 2020. "The Spatial Dimension of Income Inequality: An Analysis at Municipal Level," Sustainability, MDPI, vol. 12(4), pages 1-18, February.
    2. Maha A Aldahlan & Farrukh Jamal & Christophe Chesneau & Ibrahim Elbatal & Mohammed Elgarhy, 2020. "Exponentiated power generalized Weibull power series family of distributions: Properties, estimation and applications," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-25, March.
    3. Nadezhda Gribkova & Ričardas Zitikis, 2019. "Weighted allocations, their concomitant-based estimators, and asymptotics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(4), pages 811-835, August.
    4. Debora Daniela Escobar & Georg Ch. Pflug, 2020. "The distortion principle for insurance pricing: properties, identification and robustness," Annals of Operations Research, Springer, vol. 292(2), pages 771-794, September.
    5. Daniela Escobar & Georg Pflug, 2018. "The distortion principle for insurance pricing: properties, identification and robustness," Papers 1809.06592, arXiv.org.
    6. Hai-Yan Yu & Jing-Jing Chen & Jying-Nan Wang & Ya-Ling Chiu & Hang Qiu & Li-Ya Wang, 2019. "Identification of the Differential Effect of City-Level on the Gini Coefficient of Health Service Delivery in Online Health Community," IJERPH, MDPI, vol. 16(13), pages 1-18, June.
    7. Antonia Castaño-Martínez & Gema Pigueiras & Georgios Psarrakos & Miguel A. Sordo, 2020. "Increasing concave orderings of linear combinations of order statistics with applications to social welfare," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(6), pages 699-712, August.
    8. Satya R. Chakravarty & Palash Sarkar, 2021. "An inequality paradox: relative versus absolute indices?," METRON, Springer;Sapienza Università di Roma, vol. 79(2), pages 241-254, August.

  6. García-Escudero, Luis Angel & Gordaliza, Alfonso & Greselin, Francesca & Ingrassia, Salvatore & Mayo-Iscar, Agustín, 2016. "The joint role of trimming and constraints in robust estimation for mixtures of Gaussian factor analyzers," Computational Statistics & Data Analysis, Elsevier, vol. 99(C), pages 131-147.

    Cited by:

    1. Andrea Cappozzo & Francesca Greselin & Thomas Brendan Murphy, 2020. "A robust approach to model-based classification based on trimming and constraints," 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. 14(2), pages 327-354, June.
    2. Francesca Torti & Domenico Perrotta & Marco Riani & Andrea Cerioli, 2019. "Assessing trimming methodologies for clustering linear regression data," 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. 13(1), pages 227-257, March.
    3. Luis Angel García-Escudero & Alfonso Gordaliza & Francesca Greselin & Salvatore Ingrassia & Agustín Mayo-Iscar, 2018. "Eigenvalues and constraints in mixture modeling: geometric and computational issues," 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. 12(2), pages 203-233, June.
    4. Kasa, Siva Rajesh & Rajan, Vaibhav, 2022. "Improved Inference of Gaussian Mixture Copula Model for Clustering and Reproducibility Analysis using Automatic Differentiation," Econometrics and Statistics, Elsevier, vol. 22(C), pages 67-97.

  7. Greselin Francesca, 2014. "More Equal and Poorer, or Richer but More Unequal?," Stochastics and Quality Control, De Gruyter, vol. 29(2), pages 99-117, December.

    Cited by:

    1. Francesca Greselin & Alina Jȩdrzejczak, 2020. "Analyzing the Gender Gap in Poland and Italy, and by Regions," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 26(4), pages 433-447, November.
    2. Amparo Ba'illo & Javier C'arcamo & Carlos Mora-Corral, 2021. "Extremal points of Lorenz curves and applications to inequality analysis," Papers 2103.03286, arXiv.org.
    3. Greselin, Francesca & Zitikis, Ricardas, 2015. "Measuring economic inequality and risk: a unifying approach based on personal gambles, societal preferences and references," MPRA Paper 65892, University Library of Munich, Germany.
    4. Youri Davydov & Francesca Greselin, 2020. "Comparisons Between Poorest and Richest to Measure Inequality," Sociological Methods & Research, , vol. 49(2), pages 526-561, May.
    5. Francesca Greselin & Ričardas Zitikis, 2018. "From the Classical Gini Index of Income Inequality to a New Zenga-Type Relative Measure of Risk: A Modeller’s Perspective," Econometrics, MDPI, vol. 6(1), pages 1-20, January.

  8. Francesca Greselin & Leo Pasquazzi & Ričardas Zitikis, 2013. "Contrasting the Gini and Zenga indices of economic inequality," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(2), pages 282-297, February.

    Cited by:

    1. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2021. "The Zenga Equality Curve: A New Approach to Measuring Tax Redistribution and Progressivity," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(4), pages 950-976, December.
    2. Alex Cobham & Lukas Schlögl & Andy Sumner, 2016. "Inequality and the Tails: the Palma Proposition and Ratio," Global Policy, London School of Economics and Political Science, vol. 7(1), pages 25-36, February.
    3. Alex Cobham & Andrew Sumner, 2013. "Is it all about the tails? The Palma measure of income inequality," Working Papers 308, ECINEQ, Society for the Study of Economic Inequality.
    4. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2017. "Lorenz versus Zenga Inequality Curves: a New Approach to Measuring Tax Redistribution and Progressivity," Working papers 046, Department of Economics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.
    5. Luigi Grossi & Mauro Mussini, 2017. "Inequality in Energy Intensity in the EU-28: Evidence from a New Decomposition Method," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    6. Pasquazzi Leo & Zenga Michele, 2018. "Components of Gini, Bonferroni, and Zenga Inequality Indexes for EU Income Data," Journal of Official Statistics, Sciendo, vol. 34(1), pages 149-180, March.
    7. Alex Cobham, Andy Sumner, 2013. "Is It All About the Tails? The Palma Measure of Income Inequality-Working Paper 343," Working Papers 343, Center for Global Development.
    8. Francesca Greselin & Simone Pellegrino & Achille Vernizzi, 2020. "The Social Welfare Implications of the Zenga Index," Papers 2006.12623, arXiv.org.
    9. Satya R. Chakravarty & Palash Sarkar, 2021. "An inequality paradox: relative versus absolute indices?," METRON, Springer;Sapienza Università di Roma, vol. 79(2), pages 241-254, August.
    10. Alex Cobham & Luke Schlogl & Andy Sumner, 2015. "Inequality and the tails: The Palma proposition and ratio revised," Working Papers 366, ECINEQ, Society for the Study of Economic Inequality.
    11. Greselin, Francesca & Zitikis, Ricardas, 2015. "Measuring economic inequality and risk: a unifying approach based on personal gambles, societal preferences and references," MPRA Paper 65892, University Library of Munich, Germany.
    12. Youri Davydov & Francesca Greselin, 2020. "Comparisons Between Poorest and Richest to Measure Inequality," Sociological Methods & Research, , vol. 49(2), pages 526-561, May.
    13. Francesca Greselin & Ričardas Zitikis, 2018. "From the Classical Gini Index of Income Inequality to a New Zenga-Type Relative Measure of Risk: A Modeller’s Perspective," Econometrics, MDPI, vol. 6(1), pages 1-20, January.
    14. Alina Jędrzejczak & Dorota Pekasiewicz, 2020. "Changes in Income Distribution for Different Family Types in Poland," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 26(2), pages 135-146, May.
    15. Michele Zenga, 2016. "On the decomposition by subpopulations of the point and synthetic Zenga (2007) inequality indexes," METRON, Springer;Sapienza Università di Roma, vol. 74(3), pages 375-405, December.

  9. Francesca Greselin & Antonio Punzo, 2013. "Closed Likelihood Ratio Testing Procedures to Assess Similarity of Covariance Matrices," The American Statistician, Taylor & Francis Journals, vol. 67(3), pages 117-128, August.

    Cited by:

    1. Luca Bagnato & Antonio Punzo, 2021. "Unconstrained representation of orthogonal matrices with application to common principal components," Computational Statistics, Springer, vol. 36(2), pages 1177-1195, June.
    2. Maruotti, Antonello & Punzo, Antonio, 2017. "Model-based time-varying clustering of multivariate longitudinal data with covariates and outliers," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 475-496.
    3. Salvatore Ingrassia & Antonio Punzo & Giorgio Vittadini & Simona Minotti, 2015. "The Generalized Linear Mixed Cluster-Weighted Model," Journal of Classification, Springer;The Classification Society, vol. 32(1), pages 85-113, April.
    4. Angelo Mazza & Antonio Punzo, 2020. "Mixtures of multivariate contaminated normal regression models," Statistical Papers, Springer, vol. 61(2), pages 787-822, April.
    5. Salvatore Ingrassia & Antonio Punzo & Giorgio Vittadini & Simona Minotti, 2015. "Erratum to: The Generalized Linear Mixed Cluster-Weighted Model," Journal of Classification, Springer;The Classification Society, vol. 32(2), pages 327-355, July.
    6. Salvatore D. Tomarchio & Luca Bagnato & Antonio Punzo, 2022. "Model-based clustering via new parsimonious mixtures of heavy-tailed distributions," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(2), pages 315-347, June.
    7. Dariush Najarzadeh & Mojtaba Khazaei & Mojtaba Ganjali, 2015. "Testing for equality of ordered eigenvectors of two multivariate normal populations," METRON, Springer;Sapienza Università di Roma, vol. 73(1), pages 57-72, April.
    8. Dariush Najarzadeh, 2019. "Testing equality of standardized generalized variances of k multivariate normal populations with arbitrary dimensions," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(4), pages 593-623, December.

  10. Francesca Greselin & Salvatore Ingrassia & Antonio Punzo, 2011. "Assessing the pattern of covariance matrices via an augmentation multiple testing procedure," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(2), pages 141-170, June.

    Cited by:

    1. Luca Bagnato & Antonio Punzo, 2021. "Unconstrained representation of orthogonal matrices with application to common principal components," Computational Statistics, Springer, vol. 36(2), pages 1177-1195, June.
    2. Maruotti, Antonello & Punzo, Antonio, 2017. "Model-based time-varying clustering of multivariate longitudinal data with covariates and outliers," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 475-496.
    3. Luis Angel García-Escudero & Alfonso Gordaliza & Francesca Greselin & Salvatore Ingrassia & Agustín Mayo-Iscar, 2018. "Eigenvalues and constraints in mixture modeling: geometric and computational issues," 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. 12(2), pages 203-233, June.
    4. Salvatore Ingrassia & Simona Minotti & Giorgio Vittadini, 2012. "Local Statistical Modeling via a Cluster-Weighted Approach with Elliptical Distributions," Journal of Classification, Springer;The Classification Society, vol. 29(3), pages 363-401, October.
    5. Salvatore D. Tomarchio & Luca Bagnato & Antonio Punzo, 2022. "Model-based clustering via new parsimonious mixtures of heavy-tailed distributions," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(2), pages 315-347, June.
    6. Dariush Najarzadeh & Mojtaba Khazaei & Mojtaba Ganjali, 2015. "Testing for equality of ordered eigenvectors of two multivariate normal populations," METRON, Springer;Sapienza Università di Roma, vol. 73(1), pages 57-72, April.
    7. Dariush Najarzadeh, 2019. "Testing equality of standardized generalized variances of k multivariate normal populations with arbitrary dimensions," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(4), pages 593-623, December.

  11. Francesca Greselin & Leo Pasquazzi & Ričardas Zitikis, 2010. "Zenga's New Index of Economic Inequality, Its Estimation, and an Analysis of Incomes in Italy," Journal of Probability and Statistics, Hindawi, vol. 2010, pages 1-26, April.
    See citations under working paper version above.

More information

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (1) 2011-06-11
  2. NEP-EUR: Microeconomic European Issues (1) 2018-01-08
  3. NEP-GTH: Game Theory (1) 2015-08-19
  4. NEP-PBE: Public Economics (1) 2018-01-08
  5. NEP-PUB: Public Finance (1) 2018-01-08

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