Elena Stanghellini

Personal Details

First Name:	Elena
Middle Name:
Last Name:	Stanghellini
Suffix:
RePEc Short-ID:	pst713
	[This author has chosen not to make the email address public]
	https://www.elenastanghellini.it/
Terminal Degree:	Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti"; Università degli Studi di Firenze (from RePEc Genealogy)

Affiliation

Dipartimento di Economia
Università degli Studi di Perugia

Perugia, Italy
http://www.econ.unipg.it/
RePEc:edi:deperit (more details at EDIRC)

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. Doretti, Marco & Geneletti, Sara & Stanghellini, Elena, 2018. "Missing data: a unified taxonomy guided by conditional independence," LSE Research Online Documents on Economics 87227, London School of Economics and Political Science, LSE Library.
   • Marco Doretti & Sara Geneletti & Elena Stanghellini, 2018. "Missing Data: A Unified Taxonomy Guided by Conditional Independence," International Statistical Review, International Statistical Institute, vol. 86(2), pages 189-204, August.

   Cited by:

   1. Mehboob Ali & Göran Kauermann, 2021. "A split questionnaire survey design in the context of statistical matching," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(4), pages 1219-1236, October.
   2. Nitzan Cohen & Yakir Berchenko, 2021. "Normalized Information Criteria and Model Selection in the Presence of Missing Data," Mathematics, MDPI, vol. 9(19), pages 1-23, October.
   3. Thakur Narendra Singh & Shukla Diwakar, 2022. "Missing data estimation based on the chaining technique in survey sampling," Statistics in Transition New Series, Statistics Poland, vol. 23(4), pages 91-111, December.

2. Elena Stanghellini & Eduwin Pakpahan, 2013. "Identification of casual effects in linear models: beyond Instrumental Variables," Quaderni del Dipartimento di Economia, Finanza e Statistica 117/2013, Università di Perugia, Dipartimento Economia.
   • Elena Stanghellini & Eduwin Pakpahan, 2015. "Identification of causal effects in linear models: beyond instrumental variables," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(3), pages 489-509, September.

   Cited by:

   1. Manabu Kuroki & Hisayoshi Nanmo, 2020. "Variance formulas for estimated mean response and predicted response with external intervention based on the back-door criterion in linear structural equation models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(4), pages 667-685, December.
   2. Ryusei Shingaki & Hiroshi Kanda & Manabu Kuroki, 2021. "Selection and integration of generalized instrumental variables for estimating total effects," Statistical Papers, Springer, vol. 62(5), pages 2355-2381, October.
   3. Nanmo, Hisayoshi & Kuroki, Manabu, 2021. "Exact variance formula for the estimated mean outcome with external intervention based on the front-door criterion in Gaussian linear structural equation models," Journal of Multivariate Analysis, Elsevier, vol. 185(C).
   4. Breuer, Anita & Asiedu, Edward, 2017. "Can Gender-Targeted Employment Interventions Help Enhance Community Participation? Evidence from Urban Togo," World Development, Elsevier, vol. 96(C), pages 390-407.

3. Francesca Pierri & Alberto Burchi & Elena Stanghellini, 2011. "La capacità predittiva degli indicatori di bilancio: una verifica sulle aziende umbre," Quaderni del Dipartimento di Economia, Finanza e Statistica 92/2011, Università di Perugia, Dipartimento Economia.

   Cited by:

   1. Francesco Venturini, 2011. "Product variety, product quality, and evidence of Schumpeterian endogenous growth: a note," Quaderni del Dipartimento di Economia, Finanza e Statistica 93/2011, Università di Perugia, Dipartimento Economia.

4. Marco Nicolosi & Stefano Grassi & Elena Stanghellini, 2011. "How to measure Corporate Social Responsibility," Quaderni del Dipartimento di Economia, Finanza e Statistica 96/2011, Università di Perugia, Dipartimento Economia.

   Cited by:

   1. Leonardo Becchetti & Nazaria Solferino & Maria Elisabetta Tessitore, 2016. "Corporate social responsibility and profit volatility: theory and empirical evidence," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 25(1), pages 49-89.
      • Becchetti, Leonardo & Solferino, Nazaria & Tessitore, Maria Elisabetta, 2013. "Corporate social responsibility and profit volatility: theory and empirical evidence," AICCON Working Papers 129-2013, Associazione Italiana per la Cultura della Cooperazione e del Non Profit.

5. Elena Stanghellini & Francesco Claudio Stingo & Rosa Capobianco, 2008. "On the estimation of a binary response model in a selected population," Quaderni del Dipartimento di Economia, Finanza e Statistica 62/2008, Università di Perugia, Dipartimento Economia.

   Cited by:

   1. Prosper Dovonon & Alastair Hall & Frank Kleibergen, 2018. "Inference in Second-Order Identified Models," CIRANO Working Papers 2018s-36, CIRANO.
   2. Mirella Damiani, 2010. "Labour regulation, corporate governance and varieties of capitalism," Quaderni del Dipartimento di Economia, Finanza e Statistica 76/2010, Università di Perugia, Dipartimento Economia.
   3. Stefano Herzel, Stefano & Marco Nicolosi, Marco & Starica, Catalin, 2010. "The cost of sustainability on optimal portfolio choices," Sustainable Investment and Corporate Governance Working Papers 2010/15, Sustainable Investment Research Platform.
      • Stefano Herzel & Marco Nicolosi & Cătălin Stărică, 2012. "The cost of sustainability in optimal portfolio decisions," The European Journal of Finance, Taylor & Francis Journals, vol. 18(3-4), pages 333-349, May.
      • Stefano Herzel & Marco Nicolosi & Catalin Starica, 2011. "The cost of sustainability on optimal portfolio choices," Quaderni del Dipartimento di Economia, Finanza e Statistica 84/2011, Università di Perugia, Dipartimento Economia.
   4. Prosper Dovonon & Alastair Hall, 2018. "The Asymptotic Properties of GMM and Indirect Inference under Second-order Identification," CIRANO Working Papers 2018s-37, CIRANO.
   5. Mirella Damiani & Fabrizio Pompei & Andrea Ricci, 2011. "Temporary job protection and productivity growth in EU economies," Quaderni del Dipartimento di Economia, Finanza e Statistica 87/2011, Università di Perugia, Dipartimento Economia.
      • Damiani, Mirella & Pompei, Fabrizio & Ricci, Andrea, 2011. "Temporary job protection and productivity growth in EU economies," MPRA Paper 29698, University Library of Munich, Germany.
   6. Prosper Dovonon & Alastair R. Hall, 2017. "The Asymptotic Properties of GMM and Indirect Inference Under Second-Order Identification," Economics Discussion Paper Series 1705, Economics, The University of Manchester.
   7. Davide Castellani & Fabio Pieri, 2011. "Foreign Investments and Productivity Evidence from European Regions," Quaderni del Dipartimento di Economia, Finanza e Statistica 83/2011, Università di Perugia, Dipartimento Economia.
   8. Silvia Micheli, 2010. "Learning Curve and Wind Power," Quaderni del Dipartimento di Economia, Finanza e Statistica 81/2010, Università di Perugia, Dipartimento Economia.
   9. Francesco Venturini, 2011. "Product variety, product quality, and evidence of Schumpeterian endogenous growth: a note," Quaderni del Dipartimento di Economia, Finanza e Statistica 93/2011, Università di Perugia, Dipartimento Economia.

Articles

1. De Novellis, G. & Musile Tanzi, P. & Ranalli, M.G. & Stanghellini, E., 2024. "Leveraged finance exposure in the banking system: Systemic risk and interconnectedness," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).

   Cited by:

   1. De Novellis, G. & Musile Tanzi, P. & Stanghellini, E., 2024. "Covenant-lite agreement and credit risk: A key relationship in the leveraged loan market," Research in International Business and Finance, Elsevier, vol. 70(PB).

2. Marco Doretti & Martina Raggi & Elena Stanghellini, 2022. "Exact parametric causal mediation analysis for a binary outcome with a binary mediator," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(1), pages 87-108, March.

   Cited by:

   1. Chiara Di Maria & Claudio Rubino & Alessandro Albano, 2024. "The derivative-based approach to nonlinear mediation models: insights and applications," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(5), pages 4383-4405, October.
   2. Caubet, Miguel & Samoilenko, Mariia & Drouin, Simon & Sinnett, Daniel & Krajinovic, Maja & Laverdière, Caroline & Marcil, Valérie & Lefebvre, Geneviève, 2023. "Bayesian joint modeling for causal mediation analysis with a binary outcome and a binary mediator: Exploring the role of obesity in the association between cranial radiation therapy for childhood acut," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).

3. Marco Doretti & Sara Geneletti & Elena Stanghellini, 2018. "Missing Data: A Unified Taxonomy Guided by Conditional Independence," International Statistical Review, International Statistical Institute, vol. 86(2), pages 189-204, August.
   • Doretti, Marco & Geneletti, Sara & Stanghellini, Elena, 2018. "Missing data: a unified taxonomy guided by conditional independence," LSE Research Online Documents on Economics 87227, London School of Economics and Political Science, LSE Library.
   See citations under working paper version above.
4. Minna Genbäck & Nawi Ng & Elena Stanghellini & Xavier de Luna, 2018. "Predictors of decline in self-reported health: addressing non-ignorable dropout in longitudinal studies of aging," European Journal of Ageing, Springer, vol. 15(2), pages 211-220, June.

   Cited by:

   1. Anita Lindmark, 2022. "Sensitivity analysis for unobserved confounding in causal mediation analysis allowing for effect modification, censoring and truncation," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 785-814, October.

5. Fabrizia Mealli & Barbara Pacini & Elena Stanghellini, 2016. "Identification of Principal Causal Effects Using Additional Outcomes in Concentration Graphs," Journal of Educational and Behavioral Statistics, , vol. 41(5), pages 463-480, October.

   Cited by:

   1. Silvia Noirjean & Mario Biggeri & Laura Forastiere & Fabrizia Mealli & Maria Nannini, 2023. "Estimating causal effects of community health financing via principal stratification," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(4), pages 1317-1350, October.
   2. Lupparelli, Monia & Mattei, Alessandra, 2020. "Joint and marginal causal effects for binary non-independent outcomes," Journal of Multivariate Analysis, Elsevier, vol. 178(C).
   3. Avi Feller & Fabrizia Mealli & Luke Miratrix, 2017. "Principal Score Methods: Assumptions, Extensions, and Practical Considerations," Journal of Educational and Behavioral Statistics, , vol. 42(6), pages 726-758, December.

6. Elena Stanghellini & Eduwin Pakpahan, 2015. "Identification of causal effects in linear models: beyond instrumental variables," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(3), pages 489-509, September.
   • Elena Stanghellini & Eduwin Pakpahan, 2013. "Identification of casual effects in linear models: beyond Instrumental Variables," Quaderni del Dipartimento di Economia, Finanza e Statistica 117/2013, Università di Perugia, Dipartimento Economia.
   See citations under working paper version above.
7. Minna Genbäck & Elena Stanghellini & Xavier Luna, 2015. "Uncertainty intervals for regression parameters with non-ignorable missingness in the outcome," Statistical Papers, Springer, vol. 56(3), pages 829-847, August.

   Cited by:

   1. Fayyaz Bahari & Safar Parsi & Mojtaba Ganjali, 2021. "Empirical likelihood inference in general linear model with missing values in response and covariates by MNAR mechanism," Statistical Papers, Springer, vol. 62(2), pages 591-622, April.
   2. Minna Genbäck & Nawi Ng & Elena Stanghellini & Xavier de Luna, 2018. "Predictors of decline in self-reported health: addressing non-ignorable dropout in longitudinal studies of aging," European Journal of Ageing, Springer, vol. 15(2), pages 211-220, June.
   3. Marco Doretti & Martina Raggi & Elena Stanghellini, 2022. "Exact parametric causal mediation analysis for a binary outcome with a binary mediator," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(1), pages 87-108, March.
   4. Anita Lindmark, 2022. "Sensitivity analysis for unobserved confounding in causal mediation analysis allowing for effect modification, censoring and truncation," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 785-814, October.
   5. Fayyaz Bahari & Safar Parsi & Mojtaba Ganjali, 2021. "Goodness of fit test for general linear model with nonignorable missing on response variable," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(1), pages 163-196, March.
   6. Emmanuel O. Ogundimu, 2022. "Regularization and variable selection in Heckman selection model," Statistical Papers, Springer, vol. 63(2), pages 421-439, April.
   7. Gorbach, Tetiana & de Luna, Xavier, 2018. "Inference for partial correlation when data are missing not at random," Statistics & Probability Letters, Elsevier, vol. 141(C), pages 82-89.

8. Allman Elizabeth S. & Rhodes John A. & Stanghellini Elena & Valtorta Marco, 2015. "Parameter Identifiability of Discrete Bayesian Networks with Hidden Variables," Journal of Causal Inference, De Gruyter, vol. 3(2), pages 189-205, September.

   Cited by:

   1. Fabrizia Mealli & Barbara Pacini & Elena Stanghellini, 2016. "Identification of Principal Causal Effects Using Additional Outcomes in Concentration Graphs," Journal of Educational and Behavioral Statistics, , vol. 41(5), pages 463-480, October.

9. Nicola Falocci & Renato Paniccià & Elena Stanghellini, 2009. "Regression modelling of the flows in an input–output table with accounting constraints," Statistical Papers, Springer, vol. 50(2), pages 373-382, March.

   Cited by:

   1. Galli, Paolo & Fraga, Carla & de Sequeira Santos, Marcio Peixoto, 2016. "Gravitational force exerted by Brazilian tourist destinations on foreign air travelers," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 76-83.
   2. Michael Pfaffermayr, 2018. "Trade creation and trade diversion of regional trade agreements revisited: A constrained panel pseudo-maximum likelihood approach," Working Papers 2018-10, Faculty of Economics and Statistics, Universität Innsbruck.

10. Marchetti, Giovanni M. & Stanghellini, Elena, 2008. "A note on distortions induced by truncation with applications to linear regression systems," Statistics & Probability Letters, Elsevier, vol. 78(6), pages 824-829, April.

    Cited by:

    1. Young, Phil D. & Kahle, David J. & Young, Dean M., 2017. "On the independence of singular multivariate skew-normal sub-vectors," Statistics & Probability Letters, Elsevier, vol. 122(C), pages 58-62.
    2. Elena Stanghellini, 2012. "Comments on: Sequence of regressions and their independences," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(2), pages 265-267, June.

11. Elena Stanghellini & Nanny Wermuth, 2005. "On the identification of path analysis models with one hidden variable," Biometrika, Biometrika Trust, vol. 92(2), pages 337-350, June.

    Cited by:

    1. Elena Stanghellini & Eduwin Pakpahan, 2013. "Identification of casual effects in linear models: beyond Instrumental Variables," Quaderni del Dipartimento di Economia, Finanza e Statistica 117/2013, Università di Perugia, Dipartimento Economia.
       • Elena Stanghellini & Eduwin Pakpahan, 2015. "Identification of causal effects in linear models: beyond instrumental variables," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(3), pages 489-509, September.
    2. Nanny Wermuth & Kayvan Sadeghi, 2012. "Sequences of regressions and their independences," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(2), pages 215-252, June.
    3. Giovanni Porzio & Maria Vitale, 2007. "Exploring Nonlinearities in Path Models," Quality & Quantity: International Journal of Methodology, Springer, vol. 41(6), pages 937-954, December.
    4. Burkhard Raunig, 2019. "Background Indicators," Econometrics, MDPI, vol. 7(2), pages 1-14, May.
       • Burkhard Raunig, 2016. "Background Indicators," Working Papers 204, Oesterreichische Nationalbank (Austrian Central Bank).
    5. Manabu Kuroki, 2016. "The Identification of Direct and Indirect Effects in Studies with an Unmeasured Intermediate Variable," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(1), pages 228-245, March.

12. Elena Stanghellini & Peter G. M. van der Heijden, 2004. "A Multiple-Record Systems Estimation Method that Takes Observed and Unobserved Heterogeneity into Account," Biometrics, The International Biometric Society, vol. 60(2), pages 510-516, June.

    Cited by:

    1. Baffour Bernard & Brown James J. & Smith Peter W.F., 2021. "Latent Class Analysis for Estimating an Unknown Population Size – with Application to Censuses," Journal of Official Statistics, Sciendo, vol. 37(3), pages 673-697, September.
    2. Shira Mitchell & Al Ozonoff & Alan M. Zaslavsky & Bethany Hedt-Gauthier & Kristian Lum & Brent A. Coull, 2013. "A Comparison of Marginal and Conditional Models for Capture–Recapture Data with Application to Human Rights Violations Data," Biometrics, The International Biometric Society, vol. 69(4), pages 1022-1032, December.
    3. Francesco Bartolucci & Fulvia Pennoni, 2007. "A Class of Latent Markov Models for Capture–Recapture Data Allowing for Time, Heterogeneity, and Behavior Effects," Biometrics, The International Biometric Society, vol. 63(2), pages 568-578, June.
    4. Peter G. M. van der Heijden & Maarten Cruyff & Paul A. Smith & Christine Bycroft & Patrick Graham & Nathaniel Matheson‐Dunning, 2022. "Multiple system estimation using covariates having missing values and measurement error: Estimating the size of the Māori population in New Zealand," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(1), pages 156-177, January.
    5. Danilo Fegatelli & Luca Tardella, 2013. "Improved inference on capture recapture models with behavioural effects," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(1), pages 45-66, March.
    6. Na You & Chang Xuan Mao, 2008. "Population Size Estimation in a Two-List Surveillance System with a Discrete Covariate," Biometrics, The International Biometric Society, vol. 64(2), pages 371-376, June.
    7. R. King & S. P. Brooks, 2008. "On the Bayesian Estimation of a Closed Population Size in the Presence of Heterogeneity and Model Uncertainty," Biometrics, The International Biometric Society, vol. 64(3), pages 816-824, September.
    8. Di Cecco Davide & Di Zio Marco & Filipponi Danila & Rocchetti Irene, 2018. "Population Size Estimation Using Multiple Incomplete Lists with Overcoverage," Journal of Official Statistics, Sciendo, vol. 34(2), pages 557-572, June.
    9. Thandrayen, Joanne & Wang, Yan, 2009. "A latent variable regression model for capture-recapture data," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2740-2746, May.

13. A. Capitanio & A. Azzalini & E. Stanghellini, 2003. "Graphical models for skew‐normal variates," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 30(1), pages 129-144, March.

    Cited by:

    1. Azzalini, Adelchi, 2022. "An overview on the progeny of the skew-normal family— A personal perspective," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    2. Reinaldo B. Arellano-Valle & Adelchi Azzalini, 2022. "Some properties of the unified skew-normal distribution," Statistical Papers, Springer, vol. 63(2), pages 461-487, April.
    3. Jorge M. Arevalillo & Hilario Navarro, 2020. "Data projections by skewness maximization under scale mixtures of skew-normal vectors," 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 435-461, June.
    4. David Mayston, 2015. "Analysing the effectiveness of public service producers with endogenous resourcing," Journal of Productivity Analysis, Springer, vol. 44(1), pages 115-126, August.
    5. Jorge M. Arevalillo & Hilario Navarro, 2019. "A stochastic ordering based on the canonical transformation of skew-normal vectors," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 475-498, June.
    6. Naderi, Mehrdad & Mirfarah, Elham & Wang, Wan-Lun & Lin, Tsung-I, 2023. "Robust mixture regression modeling based on the normal mean-variance mixture distributions," Computational Statistics & Data Analysis, Elsevier, vol. 180(C).
    7. Katherine Elizabeth Castellano & Andrew Dean Ho, 2013. "Contrasting OLS and Quantile Regression Approaches to Student “Growth†Percentiles," Journal of Educational and Behavioral Statistics, , vol. 38(2), pages 190-215, April.
    8. Ahmed Hossain & Joseph Beyene, 2015. "Application of skew-normal distribution for detecting differential expression to microRNA data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(3), pages 477-491, March.
    9. Djordjilović, Vera & Chiogna, Monica, 2022. "Searching for a source of difference in graphical models," Journal of Multivariate Analysis, Elsevier, vol. 190(C).
    10. Arellano-Valle, Reinaldo B. & Azzalini, Adelchi, 2008. "The centred parametrization for the multivariate skew-normal distribution," Journal of Multivariate Analysis, Elsevier, vol. 99(7), pages 1362-1382, August.
    11. Reinaldo B. Arellano-Valle & Marc G. Genton, 2010. "Multivariate extended skew-t distributions and related families," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 201-234.
    12. Christian E. Galarza & Larissa A. Matos & Victor H. Lachos, 2022. "An EM algorithm for estimating the parameters of the multivariate skew-normal distribution with censored responses," METRON, Springer;Sapienza Università di Roma, vol. 80(2), pages 231-253, August.
    13. Sheng, Tianhong & Li, Bing & Solea, Eftychia, 2023. "On skewed Gaussian graphical models," Journal of Multivariate Analysis, Elsevier, vol. 194(C).
    14. Christopher J. Adcock, 2022. "Properties and Limiting Forms of the Multivariate Extended Skew-Normal and Skew-Student Distributions," Stats, MDPI, vol. 5(1), pages 1-42, March.
    15. Contreras-Reyes, Javier E., 2015. "Rényi entropy and complexity measure for skew-gaussian distributions and related families," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 84-91.
    16. Young, Phil D. & Kahle, David J. & Young, Dean M., 2017. "On the independence of singular multivariate skew-normal sub-vectors," Statistics & Probability Letters, Elsevier, vol. 122(C), pages 58-62.
    17. Anna Gottard & Simona Pacillo, 2007. "On the impact of contaminations in graphical Gaussian models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 15(3), pages 343-354, February.
    18. Marchetti, Giovanni M. & Stanghellini, Elena, 2008. "A note on distortions induced by truncation with applications to linear regression systems," Statistics & Probability Letters, Elsevier, vol. 78(6), pages 824-829, April.
    19. Mondal, Sagnik & Genton, Marc G., 2024. "A multivariate skew-normal-Tukey-h distribution," Journal of Multivariate Analysis, Elsevier, vol. 200(C).
    20. Antonio Canale & Euloge Clovis Kenne Pagui & Bruno Scarpa, 2016. "Bayesian modeling of university first-year students' grades after placement test," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(16), pages 3015-3029, December.
    21. Raúl Alejandro Morán-Vásquez & Anlly Daniela Giraldo-Melo & Mauricio A. Mazo-Lopera, 2023. "Quantile Estimation Using the Log-Skew-Normal Linear Regression Model with Application to Children’s Weight Data," Mathematics, MDPI, vol. 11(17), pages 1-10, August.
    22. Mahdi Salehi & Mahdi Doostparast, 2015. "Expressions for moments of order statistics and records from the skew-normal distribution in terms of multivariate normal orthant probabilities," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(4), pages 547-568, November.
    23. Anna Gottard & Simona Pacillo, 2007. "On the impact of contaminations in graphical Gaussian models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 15(3), pages 343-354, February.
    24. Karoline Bax & Emanuele Taufer & Sandra Paterlini, 2022. "A generalized precision matrix for t-Student distributions in portfolio optimization," Papers 2203.13740, arXiv.org.
    25. Zareifard, Hamid & Rue, Håvard & Khaledi, Majid Jafari & Lindgren, Finn, 2016. "A skew Gaussian decomposable graphical model," Journal of Multivariate Analysis, Elsevier, vol. 145(C), pages 58-72.
    26. Adelchi Azzalini & Antonella Bacchieri, 2010. "A prospective combination of phase II and phase III in drug development," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 347-369.

14. Elena Stanghellini, 2003. "Monitoring the Behaviour of Credit Card Holders with Graphical Chain Models," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 30(9‐10), pages 1423-1435, December.

    Cited by:

    1. Ann Shawing Yang, 2015. "Lottery Payment Cards: A Study of Mental Accounting," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 22(3), pages 201-226, July.

15. Paolo Giudici & Elena Stanghellini, 2001. "Bayesian inference for graphical factor analysis models," Psychometrika, Springer;The Psychometric Society, vol. 66(4), pages 577-591, December.

    Cited by:

    1. Giudici, Paolo, 2018. "Financial data science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 160-164.
    2. Claudia Tarantola & Paola Vicard, 2002. "Spanning trees and identifiability of a single-factor model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(2), pages 139-152, June.

16. E. Stanghellini & K. J. McConway & D. J. Hand, 1999. "A Discrete Variable Chain Graph for Applicants for Credit," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 48(2), pages 239-251.

    Cited by:

    1. Frank Fabozzi & Omar Masood & Radu Tunaru, 2007. "Discrete Variable Chain Graphical Modelling for Assessing the Effects of Fund Managers' Characteristics on Incentives Satisfaction and Size of Returns," The European Journal of Finance, Taylor & Francis Journals, vol. 13(3), pages 269-282.
    2. L C Thomas & R W Oliver & D J Hand, 2005. "A survey of the issues in consumer credit modelling research," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(9), pages 1006-1015, September.
    3. Elena Stanghellini, 2003. "Monitoring the Behaviour of Credit Card Holders with Graphical Chain Models," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 30(9‐10), pages 1423-1435, December.

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 2 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-BEC: Business Economics (1) 2012-01-25
2. NEP-ECM: Econometrics (1) 2019-01-07
3. NEP-MKT: Marketing (1) 2012-01-25

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Please note that most corrections can take a couple of weeks to filter through the various RePEc services.