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Brunero Liseo

Personal Details

First Name:Brunero
Middle Name:
Last Name:Liseo
Suffix:
RePEc Short-ID:pli1596
[This author has chosen not to make the email address public]
https://bruneroliseo.site.uniroma1.it/

Affiliation

Dipartimento di Metodi e modelli per l'economia, il territorio e la finanza (MEMOTEF)
Facoltà di Economia
"Sapienza" Università di Roma

Roma, Italy
https://web.uniroma1.it/memotef/
RePEc:edi:dmrosit (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Nicola Acocella & Giorgio Alleva & Elton Beqiraj & Giovanni Di Bartolomeo & Fabio Di Dio & Marco Di Pietro & Francesco Felici & Brunero Liseo, 2018. "A stochastic estimated version of the Italian dynamic General Equilibrium Model (IGEM)," Working Papers 3, Department of the Treasury, Ministry of the Economy and of Finance.
  2. Judith Rousseau & Nicolas Chopin & Brunero Liseo, 2010. "Bayesian Nonparametric Estimation of the Spectral Density of a Long or Intermediate Memory Gaussian Process," Working Papers 2010-38, Center for Research in Economics and Statistics.

Articles

  1. Bufalo, Michele & Liseo, Brunero & Orlando, Giuseppe, 2025. "Skew–Brownian processes for estimating the volatility of crude oil Brent," International Journal of Forecasting, Elsevier, vol. 41(2), pages 763-780.
  2. Nina Deliu & Brunero Liseo, 2025. "A copula-based Bayesian framework for doping detection," Computational Statistics, Springer, vol. 40(4), pages 1873-1898, April.
  3. Marco Di Zio & Brunero Liseo & Maria Giovanna Ranalli, 2024. "Bayesian Ideas in Survey Sampling: The Legacy of Basu," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 86(1), pages 71-94, November.
  4. Lyubov Doroshenko & Brunero Liseo, 2023. "Generalized linear mixed model with bayesian rank likelihood," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(2), pages 425-446, June.
  5. Diego Battagliese & Clara Grazian & Brunero Liseo & Cristiano Villa, 2023. "Copula modelling with penalized complexity priors: the bivariate case," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(2), pages 542-565, June.
  6. Paolo Onorati & Brunero Liseo, 2022. "Bayesian Hierarchical Copula Models with a Dirichlet–Laplace Prior," Stats, MDPI, vol. 5(4), pages 1-17, November.
  7. Grazian, Clara & Dalla Valle, Luciana & Liseo, Brunero, 2022. "Approximate Bayesian conditional copulas," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
  8. Acocella, Nicola & Beqiraj, Elton & Di Bartolomeo, Giovanni & Di Pietro, Marco & Felici, Francesco & Alleva, Giorgio & Di Dio, Fabio & Liseo, Brunero, 2020. "A stochastic estimated version of the Italian dynamic General Equilibrium Model," Economic Modelling, Elsevier, vol. 92(C), pages 339-357.
  9. Grazian, Clara & Villa, Cristiano & Liseo, Brunero, 2020. "On a loss-based prior for the number of components in mixture models," Statistics & Probability Letters, Elsevier, vol. 158(C).
  10. Hao Ji & Hao Wang & Jia Xu & Brunero Liseo, 2020. "Dependence Structure between China’s Stock Market and Other Major Stock Markets before and after the 2008 Financial Crisis," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(11), pages 2608-2624, September.
  11. Clara Grazian & Fabrizio Leisen & Brunero Liseo, 2019. "Modelling preference data with the Wallenius distribution," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(2), pages 541-558, February.
  12. Brunero Liseo, 2019. "Discussion on prior-based Bayes information criterion," Statistical Theory and Related Fields, Taylor & Francis Journals, vol. 3(1), pages 22-23, January.
  13. Hao Ji & Hao Wang & Brunero Liseo, 2018. "Portfolio Diversification Strategy Via Tail‐Dependence Clustering and ARMA‐GARCH Vine Copula Approach," Australian Economic Papers, Wiley Blackwell, vol. 57(3), pages 265-283, September.
  14. Serena Arima & William R. Bell & Gauri S. Datta & Carolina Franco & Brunero Liseo, 2017. "Multivariate Fay–Herriot Bayesian estimation of small area means under functional measurement error," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(4), pages 1191-1209, October.
  15. Clara Grazian & Brunero Liseo, 2015. "Approximate Bayesian Computation for Copula Estimation," Statistica, Department of Statistics, University of Bologna, vol. 75(1), pages 111-127.
  16. Serena Arima & Gauri S. Datta & Brunero Liseo, 2015. "Bayesian Estimators for Small Area Models when Auxiliary Information is Measured with Error," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(2), pages 518-529, June.
  17. Andrea Tancredi & Brunero Liseo, 2015. "Regression analysis with linked data: problems and possible solutions," Statistica, Department of Statistics, University of Bologna, vol. 75(1), pages 19-35.
  18. Muhammad Naeem & Hao Ji & Brunero Liseo, 2014. "Negative Return-Volume Relationship in Asian Stock Markets: Figarch-Copula Approach," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 2(2), pages 1-20.
  19. Rubio, Francisco Javier & Liseo, Brunero, 2014. "On the independence Jeffreys prior for skew-symmetric models," Statistics & Probability Letters, Elsevier, vol. 85(C), pages 91-97.
  20. Marcia D'Elia Branco & Marc G. Genton & Brunero Liseo, 2013. "Objective Bayesian Analysis of Skew-t Distributions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(1), pages 63-85, March.
  21. Liseo, Brunero & Parisi, Antonio, 2013. "Bayesian inference for the multivariate skew-normal model: A population Monte Carlo approach," Computational Statistics & Data Analysis, Elsevier, vol. 63(C), pages 125-138.
  22. Fabrizio Solari & Brunero Liseo & Dongchu Sun, 2008. "Some remarks on Bayesian inference for one-way ANOVA models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(3), pages 483-498, September.
  23. Brunero Liseo, 2003. "Bayesian and conditional frequentist analyses of the Fieller’s problem. A critical review," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 133-150.
  24. Liseo, Brunero & Loperfido, Nicola, 2003. "A Bayesian interpretation of the multivariate skew-normal distribution," Statistics & Probability Letters, Elsevier, vol. 61(4), pages 395-401, February.

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. Nicola Acocella & Giorgio Alleva & Elton Beqiraj & Giovanni Di Bartolomeo & Fabio Di Dio & Marco Di Pietro & Francesco Felici & Brunero Liseo, 2018. "A stochastic estimated version of the Italian dynamic General Equilibrium Model (IGEM)," Working Papers 3, Department of the Treasury, Ministry of the Economy and of Finance.

    Cited by:

    1. Acocella, Nicola & Beqiraj, Elton & Di Bartolomeo, Giovanni & Di Pietro, Marco & Felici, Francesco, 2020. "An evaluation of alternative fiscal adjustment plans: The case of Italy," Journal of Policy Modeling, Elsevier, vol. 42(3), pages 699-711.
    2. Acocella, Nicola & Beqiraj, Elton & Di Bartolomeo, Giovanni & Di Pietro, Marco & Felici, Francesco & Alleva, Giorgio & Di Dio, Fabio & Liseo, Brunero, 2020. "A stochastic estimated version of the Italian dynamic General Equilibrium Model," Economic Modelling, Elsevier, vol. 92(C), pages 339-357.
    3. Acocella Nicola & Beqiraj Elton & Di Bartolomeo Giovanni & Di Pietro Marco & Felici Francesco, 2020. "An evaluation of alternative fiscal adjustment plans," wp.comunite 00149, Department of Communication, University of Teramo.

  2. Judith Rousseau & Nicolas Chopin & Brunero Liseo, 2010. "Bayesian Nonparametric Estimation of the Spectral Density of a Long or Intermediate Memory Gaussian Process," Working Papers 2010-38, Center for Research in Economics and Statistics.

    Cited by:

    1. Julyan Arbel & Ghislaine Gayraud & Judith Rousseau, 2013. "Bayesian Optimal Adaptive Estimation Using a Sieve prior," Working Papers 2013-19, Center for Research in Economics and Statistics.

Articles

  1. Marco Di Zio & Brunero Liseo & Maria Giovanna Ranalli, 2024. "Bayesian Ideas in Survey Sampling: The Legacy of Basu," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 86(1), pages 71-94, November.

    Cited by:

    1. Dipak Dey & Subhashis Ghosal & Tapas Samanta, 2024. "Editorial Article: Remembering D. Basu’s Legacy in Statistics," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 86(1), pages 1-7, November.

  2. Lyubov Doroshenko & Brunero Liseo, 2023. "Generalized linear mixed model with bayesian rank likelihood," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(2), pages 425-446, June.

    Cited by:

    1. Maria Iannario & Maria Kateri & Claudia Tarantola, 2024. "Modelling scale effects in rating data: a Bayesian approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(5), pages 4053-4071, October.

  3. Grazian, Clara & Dalla Valle, Luciana & Liseo, Brunero, 2022. "Approximate Bayesian conditional copulas," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).

    Cited by:

    1. Nina Deliu & Brunero Liseo, 2025. "A copula-based Bayesian framework for doping detection," Computational Statistics, Springer, vol. 40(4), pages 1873-1898, April.

  4. Acocella, Nicola & Beqiraj, Elton & Di Bartolomeo, Giovanni & Di Pietro, Marco & Felici, Francesco & Alleva, Giorgio & Di Dio, Fabio & Liseo, Brunero, 2020. "A stochastic estimated version of the Italian dynamic General Equilibrium Model," Economic Modelling, Elsevier, vol. 92(C), pages 339-357.

    Cited by:

    1. Josué Diwambuena & Raquel Fonseca & Stefan Schubert, 2023. "Labor Market Institutions, Productivity, and the Business Cycle: An Application to Italy," Cahiers de recherche / Working Papers 2302, Chaire de recherche sur les enjeux économiques intergénérationnels / Research Chair in Intergenerational Economics.
    2. Maria Cristina Barbieri Góes & Giovanna Ciaffi & Santiago José Gahn, 2025. "Le grandi Opere Pubbliche: fiscal multipliers of public infrastructure in Italy (1870–1998)," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 42(1), pages 155-180, April.

  5. Hao Ji & Hao Wang & Jia Xu & Brunero Liseo, 2020. "Dependence Structure between China’s Stock Market and Other Major Stock Markets before and after the 2008 Financial Crisis," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(11), pages 2608-2624, September.

    Cited by:

    1. Ji, Hao & Wang, Hao & Zhong, Rui & Li, Min, 2020. "China's liberalizing stock market, crude oil, and safe-haven assets: A linkage study based on a novel multivariate wavelet-vine copula approach," Economic Modelling, Elsevier, vol. 93(C), pages 187-204.
    2. Fei Su & Feifan Wang & Yahua Xu, 2025. "Economic Policy Uncertainty and Volatility Spillovers Among International Stock Market Indices During the COVID-19 Outbreak," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 32(1), pages 237-266, March.
    3. Hu, Genhua & Fan, Gang-Zhi, 2022. "Empirical evidence of risk contagion across regional housing markets in China," Economic Modelling, Elsevier, vol. 115(C).

  6. Hao Ji & Hao Wang & Brunero Liseo, 2018. "Portfolio Diversification Strategy Via Tail‐Dependence Clustering and ARMA‐GARCH Vine Copula Approach," Australian Economic Papers, Wiley Blackwell, vol. 57(3), pages 265-283, September.

    Cited by:

    1. Ji, Hao & Wang, Hao & Zhong, Rui & Li, Min, 2020. "China's liberalizing stock market, crude oil, and safe-haven assets: A linkage study based on a novel multivariate wavelet-vine copula approach," Economic Modelling, Elsevier, vol. 93(C), pages 187-204.
    2. Fuchs, Sebastian & Di Lascio, F. Marta L. & Durante, Fabrizio, 2021. "Dissimilarity functions for rank-invariant hierarchical clustering of continuous variables," Computational Statistics & Data Analysis, Elsevier, vol. 159(C).
    3. Marwa Talbi & Rihab Bedoui & Christian de Peretti & Lotfi Belkacem, 2021. "Is the role of precious metals as precious as they are? A vine copula and BiVaR approaches," Post-Print hal-03671370, HAL.
    4. Zhikai Peng & Jinchuan Ke, 2022. "Spillover Effect of the Interaction between Fintech and the Real Economy Based on Tail Risk Dependent Structure Analysis," Sustainability, MDPI, vol. 14(13), pages 1-22, June.
    5. Li, Jinchao & Wu, Qianqian & Tian, Yu & Fan, Liguo, 2021. "Monthly Henry Hub natural gas spot prices forecasting using variational mode decomposition and deep belief network," Energy, Elsevier, vol. 227(C).

  7. Serena Arima & William R. Bell & Gauri S. Datta & Carolina Franco & Brunero Liseo, 2017. "Multivariate Fay–Herriot Bayesian estimation of small area means under functional measurement error," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(4), pages 1191-1209, October.

    Cited by:

    1. Jan Pablo Burgard & María Dolores Esteban & Domingo Morales & Agustín Pérez, 2020. "A Fay–Herriot model when auxiliary variables are measured with error," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 166-195, March.
    2. Bijlsma Ineke & van den Brakel Jan & van der Velden Rolf & Allen Jim, 2020. "Estimating Literacy Levels at a Detailed Regional Level: an Application Using Dutch Data," Journal of Official Statistics, Sciendo, vol. 36(2), pages 251-274, June.
    3. María Dolores Esteban & María José Lombardía & Esther López-Vizcaíno & Domingo Morales & Agustín Pérez, 2020. "Small area estimation of proportions under area-level compositional mixed models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(3), pages 793-818, September.
    4. van den Brakel Jan & Michiels John, 2021. "Nowcasting Register Labour Force Participation Rates in Municipal Districts Using Survey Data," Journal of Official Statistics, Sciendo, vol. 37(4), pages 1009-1045, December.
    5. Jan Pablo Burgard & Domingo Morales & Anna-Lena Wölwer, 2022. "Small area estimation of socioeconomic indicators for sampled and unsampled domains," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(2), pages 287-314, June.
    6. Hao Sun & Emily Berg & Zhengyuan Zhu, 2022. "Bivariate small‐area estimation for binary and gaussian variables based on a conditionally specified model," Biometrics, The International Biometric Society, vol. 78(4), pages 1555-1565, December.
    7. Domingo Morales & Joscha Krause & Jan Pablo Burgard, 2022. "On the Use of Aggregate Survey Data for Estimating Regional Major Depressive Disorder Prevalence," Psychometrika, Springer;The Psychometric Society, vol. 87(1), pages 344-368, March.
    8. Serena Arima & Shaho Zarei, 2024. "Robust Bayesian small area estimation using the sub-Gaussian $$\alpha$$ α -stable distribution for measurement error in covariates," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 108(4), pages 777-799, December.
    9. Caio Gonçalves & Luna Hidalgo & Denise Silva & Jan van den Brakel, 2022. "Single‐month unemployment rate estimates for the Brazilian Labour Force Survey using state‐space models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1707-1732, October.
    10. Jan Pablo Burgard & Joscha Krause & Domingo Morales, 2022. "A measurement error Rao–Yu model for regional prevalence estimation over time using uncertain data obtained from dependent survey estimates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(1), pages 204-234, March.
    11. Joscha Krause & Jan Pablo Burgard & Domingo Morales, 2022. "Robust prediction of domain compositions from uncertain data using isometric logratio transformations in a penalized multivariate Fay–Herriot model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 76(1), pages 65-96, February.
    12. Charles R. Collins & Forrest Stuart & Patrick Janulis, 2022. "Policing gentrification or policing displacement? Testing the relationship between order maintenance policing and neighbourhood change in Los Angeles," Urban Studies, Urban Studies Journal Limited, vol. 59(2), pages 414-433, February.
    13. Jan Pablo Burgard & María Dolores Esteban & Domingo Morales & Agustín Pérez, 2021. "Small area estimation under a measurement error bivariate Fay–Herriot model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 79-108, March.
    14. María Dolores Esteban & María José Lombardía & Esther López-Vizcaíno & Domingo Morales & Agustín Pérez, 2023. "Small area estimation of average compositions under multivariate nested error regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(2), pages 651-676, June.

  8. Clara Grazian & Brunero Liseo, 2015. "Approximate Bayesian Computation for Copula Estimation," Statistica, Department of Statistics, University of Bologna, vol. 75(1), pages 111-127.

    Cited by:

    1. Kristin McCullough & Tatiana Dmitrieva & Nader Ebrahimi, 2022. "New approximate Bayesian computation algorithm for censored data," Computational Statistics, Springer, vol. 37(3), pages 1369-1397, July.

  9. Serena Arima & Gauri S. Datta & Brunero Liseo, 2015. "Bayesian Estimators for Small Area Models when Auxiliary Information is Measured with Error," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(2), pages 518-529, June.

    Cited by:

    1. Jan Pablo Burgard & María Dolores Esteban & Domingo Morales & Agustín Pérez, 2020. "A Fay–Herriot model when auxiliary variables are measured with error," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 166-195, March.
    2. Sugasawa, Shonosuke & Kubokawa, Tatsuya, 2017. "Transforming response values in small area prediction," Computational Statistics & Data Analysis, Elsevier, vol. 114(C), pages 47-60.
    3. Sugasawa, Shonosuke & Kubokawa, Tatsuya, 2017. "Bayesian estimators in uncertain nested error regression models," Journal of Multivariate Analysis, Elsevier, vol. 153(C), pages 52-63.
    4. Serena Arima & William R. Bell & Gauri S. Datta & Carolina Franco & Brunero Liseo, 2017. "Multivariate Fay–Herriot Bayesian estimation of small area means under functional measurement error," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(4), pages 1191-1209, October.
    5. Federico Crescenzi & Laura Neri, 2024. "Estimating fuzzy measures of deprivation at local level in Tuscany," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(6), pages 5309-5328, December.
    6. Domingo Morales & Joscha Krause & Jan Pablo Burgard, 2022. "On the Use of Aggregate Survey Data for Estimating Regional Major Depressive Disorder Prevalence," Psychometrika, Springer;The Psychometric Society, vol. 87(1), pages 344-368, March.
    7. Serena Arima & Shaho Zarei, 2024. "Robust Bayesian small area estimation using the sub-Gaussian $$\alpha$$ α -stable distribution for measurement error in covariates," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 108(4), pages 777-799, December.
    8. Shonosuke Sugasawa & Hiromasa Tamae & Tatsuya Kubokawa, 2017. "Bayesian Estimators for Small Area Models Shrinking Both Means and Variances," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(1), pages 150-167, March.
    9. Jan Pablo Burgard & María Dolores Esteban & Domingo Morales & Agustín Pérez, 2021. "Small area estimation under a measurement error bivariate Fay–Herriot model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 79-108, March.
    10. Datta, Gauri S. & Torabi, Mahmoud & Rao, J.N.K. & Liu, Benmei, 2018. "Small area estimation with multiple covariates measured with errors: A nested error linear regression approach of combining multiple surveys," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 49-59.
    11. Harm Jan Boonstra & Jan van den Brakel & Sumonkanti Das, 2021. "Multilevel time series modelling of mobility trends in the Netherlands for small domains," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 985-1007, July.
    12. Priyanka Anjoy, 2023. "Hierarchical Bayes Measurement Error Small Area Model for Estimation of Disaggregated Level Workers Mobility Pattern in India," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(2), pages 339-361, June.

  10. Andrea Tancredi & Brunero Liseo, 2015. "Regression analysis with linked data: problems and possible solutions," Statistica, Department of Statistics, University of Bologna, vol. 75(1), pages 19-35.

    Cited by:

    1. John M. Abowd & Joelle Abramowitz & Margaret C. Levenstein & Kristin McCue & Dhiren Patki & Trivellore Raghunathan & Ann M. Rodgers & Matthew D. Shapiro & Nada Wasi, 2019. "Optimal Probabilistic Record Linkage: Best Practice for Linking Employers in Survey and Administrative Data," Working Papers 19-08, Center for Economic Studies, U.S. Census Bureau.
    2. John Cuffe & Nathan Goldschlag, 2018. "Squeezing More Out of Your Data: Business Record Linkage with Python," Working Papers 18-46, Center for Economic Studies, U.S. Census Bureau.

  11. Muhammad Naeem & Hao Ji & Brunero Liseo, 2014. "Negative Return-Volume Relationship in Asian Stock Markets: Figarch-Copula Approach," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 2(2), pages 1-20.

    Cited by:

    1. Naeem, Muhammad & Umar, Zaghum & Ahmed, Sheraz & Ferrouhi, El Mehdi, 2020. "Dynamic dependence between ETFs and crude oil prices by using EGARCH-Copula approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    2. Naeem, Muhammad & Bouri, Elie & Boako, Gideon & Roubaud, David, 2020. "Tail dependence in the return-volume of leading cryptocurrencies," Finance Research Letters, Elsevier, vol. 36(C).

  12. Rubio, Francisco Javier & Liseo, Brunero, 2014. "On the independence Jeffreys prior for skew-symmetric models," Statistics & Probability Letters, Elsevier, vol. 85(C), pages 91-97.

    Cited by:

    1. Li, W. & Rubio, F.J., 2022. "On a prior based on the Wasserstein information matrix," Statistics & Probability Letters, Elsevier, vol. 190(C).

  13. Marcia D'Elia Branco & Marc G. Genton & Brunero Liseo, 2013. "Objective Bayesian Analysis of Skew-t Distributions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(1), pages 63-85, 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. Liseo, Brunero & Parisi, Antonio, 2013. "Bayesian inference for the multivariate skew-normal model: A population Monte Carlo approach," Computational Statistics & Data Analysis, Elsevier, vol. 63(C), pages 125-138.

  14. Liseo, Brunero & Parisi, Antonio, 2013. "Bayesian inference for the multivariate skew-normal model: A population Monte Carlo approach," Computational Statistics & Data Analysis, Elsevier, vol. 63(C), pages 125-138.

    Cited by:

    1. Hok Shing Kwong & Saralees Nadarajah, 2022. "A New Robust Class of Skew Elliptical Distributions," Methodology and Computing in Applied Probability, Springer, vol. 24(3), pages 1669-1691, September.
    2. Lin, Edward M.H. & Sun, Edward W. & Yu, Min-Teh, 2020. "Behavioral data-driven analysis with Bayesian method for risk management of financial services," International Journal of Production Economics, Elsevier, vol. 228(C).
    3. Antonio Parisi & B. Liseo, 2018. "Objective Bayesian analysis for the multivariate skew-t model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(2), pages 277-295, June.
    4. Guljanov, Gaygysyz & Mutschler, Willi & Trede, Mark, 2022. "Pruned Skewed Kalman Filter and Smoother: With Application to the Yield Curve," Dynare Working Papers 78, CEPREMAP.

  15. Brunero Liseo, 2003. "Bayesian and conditional frequentist analyses of the Fieller’s problem. A critical review," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 133-150.

    Cited by:

    1. Zhao, Guimei & Xu, Xingzhong, 2014. "The one-sided posterior predictive p-value for Fieller’s problem," Statistics & Probability Letters, Elsevier, vol. 95(C), pages 57-62.

  16. Liseo, Brunero & Loperfido, Nicola, 2003. "A Bayesian interpretation of the multivariate skew-normal distribution," Statistics & Probability Letters, Elsevier, vol. 61(4), pages 395-401, February.

    Cited by:

    1. Dey, Dipak K. & Liu, Junfeng, 2005. "A new construction for skew multivariate distributions," Journal of Multivariate Analysis, Elsevier, vol. 95(2), pages 323-344, August.
    2. Azzalini, Adelchi, 2022. "An overview on the progeny of the skew-normal family— A personal perspective," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    3. 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.
    4. Ogasawara, Haruhiko, 2021. "A non-recursive formula for various moments of the multivariate normal distribution with sectional truncation," Journal of Multivariate Analysis, Elsevier, vol. 183(C).
    5. A. Ghalamfarsa Mostofi & M. Kharrati-Kopaei, 2012. "Bayesian nonparametric inference for unimodal skew-symmetric distributions," Statistical Papers, Springer, vol. 53(4), pages 821-832, November.
    6. Hok Shing Kwong & Saralees Nadarajah, 2022. "A New Robust Class of Skew Elliptical Distributions," Methodology and Computing in Applied Probability, Springer, vol. 24(3), pages 1669-1691, September.
    7. Samuel Kotz & Donatella Vicari, 2005. "Survey of developments in the theory of continuous skewed distributions," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(2), pages 225-261.
    8. Taras Bodnar & Stepan Mazur & Nestor Parolya, 2019. "Central limit theorems for functionals of large sample covariance matrix and mean vector in matrix‐variate location mixture of normal distributions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 46(2), pages 636-660, June.
    9. 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.
    10. 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.
    11. Cedric Flecher & Denis Allard & Philippe Naveau, 2010. "Truncated skew-normal distributions: moments, estimation by weighted moments and application to climatic data," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 331-345.
    12. Sharon Lee & Geoffrey McLachlan, 2013. "On mixtures of skew normal and skew $$t$$ -distributions," 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. 7(3), pages 241-266, September.
    13. Jamalizadeh, A. & Balakrishnan, N., 2010. "Distributions of order statistics and linear combinations of order statistics from an elliptical distribution as mixtures of unified skew-elliptical distributions," Journal of Multivariate Analysis, Elsevier, vol. 101(6), pages 1412-1427, July.
    14. Young, Phil D. & Harvill, Jane L. & Young, Dean M., 2016. "A derivation of the multivariate singular skew-normal density function," Statistics & Probability Letters, Elsevier, vol. 117(C), pages 40-45.
    15. 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.
    16. Jamalizadeh, A. & Balakrishnan, N., 2009. "Prediction in a trivariate normal distribution via a linear combination of order statistics," Statistics & Probability Letters, Elsevier, vol. 79(21), pages 2289-2296, November.
    17. Sharon Lee & Geoffrey McLachlan, 2013. "Model-based clustering and classification with non-normal mixture distributions," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(4), pages 427-454, November.
    18. Arellano-Valle, Reinaldo B. & Genton, Marc G., 2005. "On fundamental skew distributions," Journal of Multivariate Analysis, Elsevier, vol. 96(1), pages 93-116, September.
    19. Kim, Hyoung-Moon & Ryu, Duchwan & Mallick, Bani K. & Genton, Marc G., 2014. "Mixtures of skewed Kalman filters," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 228-251.

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NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper 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-DGE: Dynamic General Equilibrium (1) 2018-04-23
  2. NEP-EEC: European Economics (1) 2018-04-23
  3. NEP-MAC: Macroeconomics (1) 2018-04-23

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