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Davy Paindaveine

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. Davy Paindaveine & Thomas Verdebout, 2019. "Inference for Spherical Location under High Concentration," Working Papers ECARES 2019-02, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Arthur Pewsey & Eduardo García-Portugués, 2021. "Recent advances in directional statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 1-58, March.

  2. Davy Paindaveine & Julien Remy & Thomas Verdebout, 2017. "Testing for Principal Component Directions under Weak Identifiability," Working Papers ECARES ECARES 2017-37, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Davy Paindaveine & Julien Remy & Thomas Verdebout, 2019. "Sign Tests for Weak Principal Directions," Working Papers ECARES 2019-01, ULB -- Universite Libre de Bruxelles.

  3. Davy Paindaveine & Germain Van Bever, 2017. "Tyler Shape Depth," Working Papers ECARES ECARES 2017-29, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Paindaveine, Davy & Van Bever, Germain, 2017. "On the maximal halfspace depth of permutation-invariant distributions on the simplex," Statistics & Probability Letters, Elsevier, vol. 129(C), pages 335-339.

  4. Davy Paindaveine & Germain Van Bever, 2017. "Halfspace Depths for Scatter, Concentration and Shape Matrices," Working Papers ECARES ECARES 2017-19, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Nagy, Stanislav, 2019. "Scatter halfspace depth for K-symmetric distributions," Statistics & Probability Letters, Elsevier, vol. 149(C), pages 171-177.
    2. Chau, Van Vinh & Ombao, Hernando & von Sachs, Rainer, 2017. "Data depth and rank-based tests for covariance and spectral density matrices," LIDAM Discussion Papers ISBA 2017019, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

  5. Giuseppe Pandolfo & Davy Paindaveine & Giovanni Porzio, 2017. "Distance-based Depths for Directional Data," Working Papers ECARES ECARES 2017-35, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Davide Buttarazzi & Giuseppe Pandolfo & Giovanni C. Porzio, 2018. "A boxplot for circular data," Biometrics, The International Biometric Society, vol. 74(4), pages 1492-1501, December.
    2. Arthur Pewsey & Eduardo García-Portugués, 2021. "Recent advances in directional statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 1-58, March.
    3. Kirschstein, Thomas & Liebscher, Steffen & Pandolfo, Giuseppe & Porzio, Giovanni C. & Ragozini, Giancarlo, 2019. "On finite-sample robustness of directional location estimators," Computational Statistics & Data Analysis, Elsevier, vol. 133(C), pages 53-75.

  6. Davy Paindaveine & Rondrotiana J Rasoafaraniaina & Thomas Verdebout, 2016. "Preliminary Test Estimation for Multi-Sample Principal Components," Working Papers ECARES ECARES 2016-39, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Shastitko. Andrey (Шаститко, Андрей) & Komkova, Anastasia Andreevna (Комкова, Анастасия Андреевна) & Kurdin, Alexander (Курдин, Александр) & Shastitko, Anastasia (Шаститко, Анастасия), 2016. "Competition Policy and Incentives for Innovation [Конкурентная Политика И Стимулы К Инновационной Деятельности]," Working Papers 1447, Russian Presidential Academy of National Economy and Public Administration.

  7. Christine Cutting & Davy Paindaveine & Thomas Verdebout, 2015. "Tests of Concentration for Low-Dimensional and High-Dimensional Directional Data," Working Papers ECARES ECARES 2015-05, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Arthur Pewsey & Eduardo García-Portugués, 2021. "Recent advances in directional statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 1-58, March.

  8. Christine Cutting & Davy Paindaveine & Thomas Verdebout, 2015. "Testing Uniformity on High-Dimensional Spheres against Contiguous Rotationally Symmetric Alternatives," Working Papers ECARES ECARES 2015-04, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Christine Cutting & Davy Paindaveine & Thomas Verdebout, 2015. "Tests of Concentration for Low-Dimensional and High-Dimensional Directional Data," Working Papers ECARES ECARES 2015-05, ULB -- Universite Libre de Bruxelles.
    2. Arthur Pewsey & Eduardo García-Portugués, 2021. "Recent advances in directional statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 1-58, March.
    3. Davy Paindaveine & Thomas Verdebout, 2017. "Detecting the Direction of a Signal on High-dimensional Spheres: Non-null and Le Cam Optimality Results," Working Papers ECARES ECARES 2017-40, ULB -- Universite Libre de Bruxelles.
    4. Anders Bredahl Kock & David Preinerstorfer, 2017. "Power in High-dimensional testing Problems," Working Papers ECARES ECARES 2017-42, ULB -- Universite Libre de Bruxelles.
    5. Eduardo Garcia-Portugues & Davy Paindaveine & Thomas Verdebout, 2020. "On optimal tests for rotational symmetry against new classes of hyperspherical distributions," Post-Print hal-03169388, HAL.

  9. Gery Geenens & Arthur Charpentier & Davy Paindaveine, 2014. "Probit Transformation for Nonparametric Kernel Estimation of the Copula Density," Working Papers ECARES ECARES 2014-23, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Zhang, Yifei & Goodwin, Barry K., 2020. "Implications of U.S. Crop Insurance -- A Perspective from Copulas," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304343, Agricultural and Applied Economics Association.
    2. Gery Geenens & Richard Dunn, 2017. "A nonparametric copula approach to conditional Value-at-Risk," Papers 1712.05527, arXiv.org, revised Oct 2019.
    3. Olivier Cabrignac & Arthur Charpentier & Ewen Gallic, 2020. "Modeling Joint Lives within Families," AMSE Working Papers 2021, Aix-Marseille School of Economics, France.
    4. Rodrigues, G.S. & Nott, David J. & Sisson, S.A., 2016. "Functional regression approximate Bayesian computation for Gaussian process density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 229-241.
    5. De Backer, Mickael & El Ghouch, Anouar & Van Keilegom, Ingrid, 2016. "Semiparametric Copula Quantile Regression for Complete or Censored Data," LIDAM Discussion Papers ISBA 2016009, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Nagler, Thomas & Czado, Claudia, 2016. "Evading the curse of dimensionality in nonparametric density estimation with simplified vine copulas," Journal of Multivariate Analysis, Elsevier, vol. 151(C), pages 69-89.
    7. Jesús Fajardo & Pedro Harmath, 2021. "Boundary estimation with the fuzzy set density estimator," METRON, Springer;Sapienza Università di Roma, vol. 79(3), pages 285-302, December.
    8. Niemierko, Rochus & Töppel, Jannick & Tränkler, Timm, 2019. "A D-vine copula quantile regression approach for the prediction of residential heating energy consumption based on historical data," Applied Energy, Elsevier, vol. 233, pages 691-708.
    9. Tim Janke & Mohamed Ghanmi & Florian Steinke, 2021. "Implicit Generative Copulas," Papers 2109.14567, arXiv.org, revised Nov 2021.
    10. Otneim, Håkon & Tjøstheim, Dag, 2016. "Non-parametric estimation of conditional densities: A new method," Discussion Papers 2016/22, Norwegian School of Economics, Department of Business and Management Science.
    11. Tepegjozova Marija & Zhou Jing & Claeskens Gerda & Czado Claudia, 2022. "Nonparametric C- and D-vine-based quantile regression," Dependence Modeling, De Gruyter, vol. 10(1), pages 1-21, January.
    12. Nagler Thomas & Czado Claudia & Schellhase Christian, 2017. "Nonparametric estimation of simplified vine copula models: comparison of methods," Dependence Modeling, De Gruyter, vol. 5(1), pages 99-120, January.

  10. Isabelle Charlier & Davy Paindaveine, 2014. "Conditional Quantile Estimation through Optimal Quantization," Working Papers ECARES ECARES 2014-28, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Charlier, Isabelle & Paindaveine, Davy & Saracco, Jérôme, 2015. "Conditional quantile estimation based on optimal quantization: From theory to practice," Computational Statistics & Data Analysis, Elsevier, vol. 91(C), pages 20-39.
    2. Isabelle Charlier & Davy Paindaveine & Jérôme Saracco, 2014. "Conditional Quantile Estimation Based on Optimal Quantization: from Theory to Practice," Working Papers ECARES ECARES 2014-39, ULB -- Universite Libre de Bruxelles.
    3. Isabelle Charlier & Davy Paindaveine & Jérôme Saracco, 2014. "QuantifQuantile; an R Package for Performing Quantile Regression through Optimal Quantization," Working Papers ECARES ECARES 2014-40, ULB -- Universite Libre de Bruxelles.
    4. Isabelle Charlier & Davy Paindaveine & Jérôme Saracco, 2016. "Multiple-Output Quantile Regression through Optimal Quantization," Working Papers ECARES ECARES 2016-18, ULB -- Universite Libre de Bruxelles.

  11. Rainer Dyckerhoff & Christophe Ley & Davy Paindaveine, 2014. "Depth-Based Runs Tests for bivariate Central Symmetry," Working Papers ECARES ECARES 2014-03, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Sladana Babic & Laetitia Gelbgras & Marc Hallin & Christophe Ley, 2019. "Optimal tests for elliptical symmetry: specified and unspecified location," Working Papers ECARES 2019-26, ULB -- Universite Libre de Bruxelles.
    2. Geraci, Marco Valerio & Garbaravičius, Tomas & Veredas, David, 2018. "Short selling in extreme events," Journal of Financial Stability, Elsevier, vol. 39(C), pages 90-103.

  12. Isabelle Charlier & Davy Paindaveine & Jérôme Saracco, 2014. "Conditional Quantile Estimation Based on Optimal Quantization: from Theory to Practice," Working Papers ECARES ECARES 2014-39, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Isabelle Charlier & Davy Paindaveine & Jérôme Saracco, 2014. "QuantifQuantile; an R Package for Performing Quantile Regression through Optimal Quantization," Working Papers ECARES ECARES 2014-40, ULB -- Universite Libre de Bruxelles.
    2. Isabelle Charlier & Davy Paindaveine & Jérôme Saracco, 2016. "Multiple-Output Quantile Regression through Optimal Quantization," Working Papers ECARES ECARES 2016-18, ULB -- Universite Libre de Bruxelles.

  13. Davy Paindaveine & Germain Van Bever, 2013. "Inference on the Shape of Elliptical Distribution Based on the MCD," Working Papers ECARES ECARES 2013-27, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Davy Paindaveine & Germain Van Bever, 2017. "Halfspace Depths for Scatter, Concentration and Shape Matrices," Working Papers ECARES ECARES 2017-19, ULB -- Universite Libre de Bruxelles.
    2. Davy Paindaveine & Germain Van Bever, 2017. "Tyler Shape Depth," Working Papers ECARES ECARES 2017-29, ULB -- Universite Libre de Bruxelles.

  14. Marc Hallin & Davy Paindaveine & Thomas Verdebout, 2013. "Efficient R-Estimation of Principal and Common Principal Components," Working Papers ECARES ECARES 2013-18, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Peter N. Posch & Daniel Ullmann & Dominik Wied, 2019. "Detecting structural changes in large portfolios," Empirical Economics, Springer, vol. 56(4), pages 1341-1357, April.
    2. Davy Paindaveine & Julien Remy & Thomas Verdebout, 2017. "Testing for Principal Component Directions under Weak Identifiability," Working Papers ECARES ECARES 2017-37, ULB -- Universite Libre de Bruxelles.
    3. Christophe Ley & Yvik Swan & Thomas Verdebout, 2017. "Efficient ANOVA for directional data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(1), pages 39-62, February.
    4. Paindaveine, Davy & Rasoafaraniaina, Rondrotiana Joséa & Verdebout, Thomas, 2017. "Preliminary test estimation for multi-sample principal components," Econometrics and Statistics, Elsevier, vol. 2(C), pages 106-116.
    5. Hallin, Marc & van den Akker, Ramon & Werker, Bas J.M., 2016. "Semiparametric error-correction models for cointegration with trends: Pseudo-Gaussian and optimal rank-based tests of the cointegration rank," Journal of Econometrics, Elsevier, vol. 190(1), pages 46-61.

  15. Davy Paindaveine & Thomas Verdebout, 2013. "Optimal Rank-Based Tests for the Location Parameter of a Rotationally Symmetric Distribution on the Hypersphere," Working Papers ECARES ECARES 2013-36, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Ley, Christophe & Verdebout, Thomas, 2017. "Skew-rotationally-symmetric distributions and related efficient inferential procedures," Journal of Multivariate Analysis, Elsevier, vol. 159(C), pages 67-81.
    2. Ley, Christophe & Paindaveine, Davy & Verdebout, Thomas, 2015. "High-dimensional tests for spherical location and spiked covariance," Journal of Multivariate Analysis, Elsevier, vol. 139(C), pages 79-91.
    3. Arthur Pewsey & Eduardo García-Portugués, 2021. "Recent advances in directional statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 1-58, March.
    4. Davy Paindaveine & Thomas Verdebout, 2017. "Detecting the Direction of a Signal on High-dimensional Spheres: Non-null and Le Cam Optimality Results," Working Papers ECARES ECARES 2017-40, ULB -- Universite Libre de Bruxelles.
    5. Christophe Ley & Thomas Verdebout, 2014. "Skew-rotsymmetric Distributions on Unit Spheres and Related Efficient Inferential Proceedures," Working Papers ECARES ECARES 2014-46, ULB -- Universite Libre de Bruxelles.
    6. Davy Paindaveine & Thomas Verdebout, 2013. "Universal Asymptotics for High-Dimensional Sign Tests," Working Papers ECARES ECARES 2013-40, ULB -- Universite Libre de Bruxelles.

  16. Davy Paindaveine & Thomas Verdebout, 2013. "Universal Asymptotics for High-Dimensional Sign Tests," Working Papers ECARES ECARES 2013-40, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Feng, Long & Sun, Fasheng, 2015. "A note on high-dimensional two-sample test," Statistics & Probability Letters, Elsevier, vol. 105(C), pages 29-36.
    2. Christine Cutting & Davy Paindaveine & Thomas Verdebout, 2015. "Testing Uniformity on High-Dimensional Spheres against Contiguous Rotationally Symmetric Alternatives," Working Papers ECARES ECARES 2015-04, ULB -- Universite Libre de Bruxelles.

  17. Davy Paindaveine & Germain Van Bever, 2012. "Nonparametrically Consistent Depth-Based Classifiers," Working Papers ECARES ECARES 2012-014, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Pavlo Mozharovskyi & Karl Mosler & Tatjana Lange, 2015. "Classifying real-world data with the $${ DD}\alpha $$ D D α -procedure," 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. 9(3), pages 287-314, September.
    2. Biau, Gérard & Devroye, Luc & Dujmović, Vida & Krzyżak, Adam, 2012. "An affine invariant k-nearest neighbor regression estimate," Journal of Multivariate Analysis, Elsevier, vol. 112(C), pages 24-34.
    3. Kotík, Lukáš & Hlubinka, Daniel, 2017. "A weighted localization of halfspace depth and its properties," Journal of Multivariate Analysis, Elsevier, vol. 157(C), pages 53-69.
    4. Davy Paindaveine & Germain Van Bever, 2017. "Halfspace Depths for Scatter, Concentration and Shape Matrices," Working Papers ECARES ECARES 2017-19, ULB -- Universite Libre de Bruxelles.
    5. Francesca Fortunato & Laura Anderlucci & Angela Montanari, 2020. "One‐class classification with application to forensic analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1227-1249, November.
    6. Vencalek, Ondrej & Pokotylo, Oleksii, 2018. "Depth-weighted Bayes classification," Computational Statistics & Data Analysis, Elsevier, vol. 123(C), pages 1-12.
    7. Nengxiang Ling & Germán Aneiros & Philippe Vieu, 2020. "kNN estimation in functional partial linear modeling," Statistical Papers, Springer, vol. 61(1), pages 423-444, February.
    8. Ondrej Vencalek & Olusola Samuel Makinde, 2021. "RR-classifier: a nonparametric classification procedure in multidimensional space based on relative ranks," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(4), pages 675-693, December.

  18. Marc Hallin & Zudi Lu & Davy Paindaveine & Miroslav Siman, 2012. "Local Constant and Local Bilinear Multiple-Output Quantile Regression," Working Papers ECARES ECARES 2012-003, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Marc Hallin & Miroslav Šiman, 2016. "Multiple-Output Quantile Regression," Working Papers ECARES ECARES 2016-03, ULB -- Universite Libre de Bruxelles.

  19. Marc Hallin & Davy Paindaveine & Thomas Verdebout, 2011. "Optimal Rank-Based Tests for Common Principal Components," Working Papers ECARES ECARES 2011-032, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Marc Hallin & Ramon van den Akker & Bas Werker, 2012. "Rank-Based Tests of the Cointegrating Rank in Semiparametric Error Correction Models," Working Papers ECARES ECARES 2012-042, ULB -- Universite Libre de Bruxelles.
    2. Hallin, M. & Werker, B.J.M. & van den Akker, R., 2015. "Optimal Pseudo-Gaussian and Rank-based Tests of the Cointegration Rank in Semiparametric Error-correction Models," Discussion Paper 2015-001, Tilburg University, Center for Economic Research.
    3. Davy Paindaveine & Julien Remy & Thomas Verdebout, 2019. "Sign Tests for Weak Principal Directions," Working Papers ECARES 2019-01, ULB -- Universite Libre de Bruxelles.
    4. Sladana Babic & Laetitia Gelbgras & Marc Hallin & Christophe Ley, 2019. "Optimal tests for elliptical symmetry: specified and unspecified location," Working Papers ECARES 2019-26, ULB -- Universite Libre de Bruxelles.
    5. Christophe Ley & Yvik Swan & Thomas Verdebout, 2017. "Efficient ANOVA for directional data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(1), pages 39-62, February.
    6. Paindaveine, Davy & Rasoafaraniaina, Rondrotiana Joséa & Verdebout, Thomas, 2017. "Preliminary test estimation for multi-sample principal components," Econometrics and Statistics, Elsevier, vol. 2(C), pages 106-116.
    7. Marc Hallin & Davy Paindaveine & Thomas Verdebout, 2013. "Efficient R-Estimation of Principal and Common Principal Components," Working Papers ECARES ECARES 2013-18, ULB -- Universite Libre de Bruxelles.
    8. Hallin, Marc & van den Akker, Ramon & Werker, Bas J.M., 2016. "Semiparametric error-correction models for cointegration with trends: Pseudo-Gaussian and optimal rank-based tests of the cointegration rank," Journal of Econometrics, Elsevier, vol. 190(1), pages 46-61.

  20. Sirkku Pauliina Ilmonen & Davy Paindaveine, 2011. "Semiparametrically Efficient Inference Based on Signed Ranks in Symmetric Independent Component Models," Working Papers ECARES ECARES 2011-003, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Joni Virta & Niko Lietzén & Pauliina Ilmonen & Klaus Nordhausen, 2021. "Fast tensorial JADE," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(1), pages 164-187, March.
    2. Bernd Funovits, 2020. "Identifiability and Estimation of Possibly Non-Invertible SVARMA Models: A New Parametrisation," Papers 2002.04346, arXiv.org, revised Feb 2021.
    3. Lee, Seonjoo & Shen, Haipeng & Truong, Young, 2021. "Sampling properties of color Independent Component Analysis," Journal of Multivariate Analysis, Elsevier, vol. 181(C).
    4. Jari Miettinen & Katrin Illner & Klaus Nordhausen & Hannu Oja & Sara Taskinen & Fabian J. Theis, 2016. "Separation of Uncorrelated Stationary time series using Autocovariance Matrices," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(3), pages 337-354, May.
    5. Paindaveine, Davy & Van Bever, Germain, 2014. "Inference on the shape of elliptical distributions based on the MCD," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 125-144.
    6. Bernd Funovits, 2019. "Identification and Estimation of SVARMA models with Independent and Non-Gaussian Inputs," Papers 1910.04087, arXiv.org.
    7. Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2022. "Moment tests of independent components," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 429-474, May.
    8. Marc Hallin & Chintan Mehta, 2013. "R-Estimation for Asymmetric Independent Component Analysis," Working Papers ECARES 2013-19, ULB -- Universite Libre de Bruxelles.
    9. Gabriele Fiorentini & Enrique Sentana, 2020. "Discrete Mixtures of Normals Pseudo Maximum Likelihood Estimators of Structural Vector Autoregressions," Working Papers wp2020_2023, CEMFI.
    10. Davy Paindaveine & Germain Van Bever, 2017. "Halfspace Depths for Scatter, Concentration and Shape Matrices," Working Papers ECARES ECARES 2017-19, ULB -- Universite Libre de Bruxelles.
    11. Marc Hallin & Simos Meintanis & Klaus Nordhausen, 2024. "Consistent Distribution–Free Affine–Invariant Tests for the Validity of Independent Component Models," Working Papers ECARES 2024-04, ULB -- Universite Libre de Bruxelles.
    12. Davy Paindaveine & Thomas Verdebout, 2011. "Rank Tests for Elliptical Graphical Modeling," Working Papers ECARES ECARES 2011-039, ULB -- Universite Libre de Bruxelles.
    13. Markku Lanne & Mika Meitz & Pentti Saikkonen, 2015. "Identification and estimation of non-Gaussian structural vector autoregressions," CREATES Research Papers 2015-16, Department of Economics and Business Economics, Aarhus University.
    14. Sebastiano Michele Zema, 2020. "Directed Acyclic Graph based Information Shares for Price Discovery," LEM Papers Series 2020/28, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

  21. Nezar Bennala & Marc Hallin & Davy Paindaveine, 2010. "Rank‐based Optimal Tests for Random Effects in Panel Data," Working Papers ECARES ECARES 2010-018, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Abdelhadi Akharif & Mohamed Fihri & Marc Hallin & Amal Mellouk, 2018. "Optimal Pseudo-Gaussian and Rank-Based Random Coefficient Detection in Multiple Regression," Working Papers ECARES 2018-39, ULB -- Universite Libre de Bruxelles.

  22. Delphine Cassart & Marc Hallin & Davy Paindaveine, 2010. "On the estimation of cross-information quantities in rank-based inference," Working Papers ECARES ECARES 2010-010, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Werker, Bas J.M. & Zhou, Bo, 2022. "Semiparametric testing with highly persistent predictors," Journal of Econometrics, Elsevier, vol. 227(2), pages 347-370.
    2. Werker, Bas J.M. & Zhou, B., 2022. "Semiparametric testing with highly persistent predictors," Other publications TiSEM 2974ce9c-97c1-44cd-9331-0, Tilburg University, School of Economics and Management.
    3. Hallin, Marc & La Vecchia, Davide, 2017. "R-estimation in semiparametric dynamic location-scale models," Journal of Econometrics, Elsevier, vol. 196(2), pages 233-247.
    4. M. Hallin & D. La Vecchia & H. Liu, 2022. "Center-Outward R-Estimation for Semiparametric VARMA Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 117(538), pages 925-938, April.
    5. Hallin, Marc & Swan, Yvik & Verdebout, Thomas & Veredas, David, 2013. "One-step R-estimation in linear models with stable errors," Journal of Econometrics, Elsevier, vol. 172(2), pages 195-204.
    6. Marc Hallin & Chintan Mehta, 2013. "R-Estimation for Asymmetric Independent Component Analysis," Working Papers ECARES 2013-19, ULB -- Universite Libre de Bruxelles.
    7. Delphine Cassart & Marc Hallin & Davy Paindaveine, 2014. "Optimal Rank Tests for Symmetry against Edgeworth-Type Alternatives," Working Papers ECARES ECARES 2014-48, ULB -- Universite Libre de Bruxelles.
    8. Marc Hallin & Davide La Vecchia, 2014. "Semiparametrically Efficient R-Estimation for Dynamic Location-Scale Models," Working Papers ECARES ECARES 2014-45, ULB -- Universite Libre de Bruxelles.

  23. Davy Paindaveine & Yvik Swan, 2009. "A stochastic analysis of some two-person sports," Working Papers ECARES 2009_025, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Christophe Ley & Yves Dominicy, 2017. "Mutual Point-winning Probabilities (MPW): a New Performance Measure for Table Tennis," Working Papers ECARES ECARES 2017-23, ULB -- Universite Libre de Bruxelles.

  24. Hannu Oja & Davy Paindaveine & Sara Taskinen, 2009. "Parametric and nonparametric test for multivariate independence in IC models," Working Papers ECARES 2009_018, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Ilmonen, Pauliina & Nevalainen, Jaakko & Oja, Hannu, 2010. "Characteristics of multivariate distributions and the invariant coordinate system," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1844-1853, December.

  25. Marc Hallin & Davy Paindaveine & Thomas Verdebout, 2009. "Optimal rank-based testing for principal component," Working Papers ECARES 2009_013, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Marc Hallin & Ramon van den Akker & Bas Werker, 2012. "Rank-Based Tests of the Cointegrating Rank in Semiparametric Error Correction Models," Working Papers ECARES ECARES 2012-042, ULB -- Universite Libre de Bruxelles.
    2. Eustasio Del Barrio & Alberto Gonzalez-Sanz & Marc Hallin, 2019. "A Note on the Regularity of Center-Outward Distribution and Quantile Functions," Working Papers ECARES 2019-33, ULB -- Universite Libre de Bruxelles.
    3. Christophe Ley & Yvik Swan & Thomas Verdebout, 2013. "Efficient ANOVA for Directional Data," Working Papers ECARES ECARES 2012-48, ULB -- Universite Libre de Bruxelles.
    4. Hallin, M. & Werker, B.J.M. & van den Akker, R., 2015. "Optimal Pseudo-Gaussian and Rank-based Tests of the Cointegration Rank in Semiparametric Error-correction Models," Discussion Paper 2015-001, Tilburg University, Center for Economic Research.
    5. Davy Paindaveine & Julien Remy & Thomas Verdebout, 2019. "Sign Tests for Weak Principal Directions," Working Papers ECARES 2019-01, ULB -- Universite Libre de Bruxelles.
    6. Sladana Babic & Laetitia Gelbgras & Marc Hallin & Christophe Ley, 2019. "Optimal tests for elliptical symmetry: specified and unspecified location," Working Papers ECARES 2019-26, ULB -- Universite Libre de Bruxelles.
    7. Davy Paindaveine & Julien Remy & Thomas Verdebout, 2017. "Testing for Principal Component Directions under Weak Identifiability," Working Papers ECARES ECARES 2017-37, ULB -- Universite Libre de Bruxelles.
    8. Christophe Ley & Yvik Swan & Thomas Verdebout, 2017. "Efficient ANOVA for directional data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(1), pages 39-62, February.
    9. Paindaveine, Davy & Rasoafaraniaina, Rondrotiana Joséa & Verdebout, Thomas, 2017. "Preliminary test estimation for multi-sample principal components," Econometrics and Statistics, Elsevier, vol. 2(C), pages 106-116.
    10. Marc Hallin & Davy Paindaveine & Thomas Verdebout, 2013. "Efficient R-Estimation of Principal and Common Principal Components," Working Papers ECARES ECARES 2013-18, ULB -- Universite Libre de Bruxelles.
    11. Davy Paindaveine & Thomas Verdebout, 2011. "Rank Tests for Elliptical Graphical Modeling," Working Papers ECARES ECARES 2011-039, ULB -- Universite Libre de Bruxelles.
    12. Hallin, Marc & van den Akker, Ramon & Werker, Bas J.M., 2016. "Semiparametric error-correction models for cointegration with trends: Pseudo-Gaussian and optimal rank-based tests of the cointegration rank," Journal of Econometrics, Elsevier, vol. 190(1), pages 46-61.
    13. Davy Paindaveine & Thomas Verdebout, 2013. "Optimal Rank-Based Tests for the Location Parameter of a Rotationally Symmetric Distribution on the Hypersphere," Working Papers ECARES ECARES 2013-36, ULB -- Universite Libre de Bruxelles.
    14. Marc Hallin & Davy Paindaveine & Thomas Verdebout, 2011. "Optimal Rank-Based Tests for Common Principal Components," Working Papers ECARES ECARES 2011-032, ULB -- Universite Libre de Bruxelles.

  26. Davy Paindaveine & Miroslav Siman, 2009. "On directional multiple-output quantile regression," Working Papers ECARES 2009_011, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Xiaohui Liu & Shihua Luo & Yijun Zuo, 2020. "Some results on the computing of Tukey’s halfspace median," Statistical Papers, Springer, vol. 61(1), pages 303-316, February.
    2. Davy Paindaveine & Miroslav Šiman, 2012. "Computing multiple-output regression quantile regions from projection quantiles," Computational Statistics, Springer, vol. 27(1), pages 29-49, March.
    3. Marc Hallin & Zudi Lu & Davy Paindaveine & Miroslav Siman, 2012. "Local Constant and Local Bilinear Multiple-Output Quantile Regression," Working Papers ECARES ECARES 2012-003, ULB -- Universite Libre de Bruxelles.
    4. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Transmission of US and EU Economic Policy Uncertainty Shock to Asian Economies in Bad and Good Times," IZA Discussion Papers 13274, Institute of Labor Economics (IZA).
    5. Michal Franta, 2023. "The Application of Multiple-Output Quantile Regression on the US Financial Cycle," Working Papers 2023/2, Czech National Bank.
    6. Marc Hallin & Davy Paindaveine & Miroslav Šiman, 2010. "Multivariate quantiles and multiple-output regression quantiles: From L1 optimization to halfspace depth," ULB Institutional Repository 2013/127979, ULB -- Universite Libre de Bruxelles.
    7. Dobrislav Dobrev∗ & Travis D. Nesmith & Dong Hwan Oh, 2017. "Accurate Evaluation of Expected Shortfall for Linear Portfolios with Elliptically Distributed Risk Factors," JRFM, MDPI, vol. 10(1), pages 1-14, February.
    8. Paola Stolfi & Mauro Bernardi & Lea Petrella, 2016. "Multivariate Method Of Simulated Quantiles," Departmental Working Papers of Economics - University 'Roma Tre' 0212, Department of Economics - University Roma Tre.
    9. Hlubinka, Daniel & Šiman, Miroslav, 2013. "On elliptical quantiles in the quantile regression setup," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 163-171.
    10. Daniel Hlubinka & Miroslav Šiman, 2015. "On generalized elliptical quantiles in the nonlinear quantile regression setup," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(2), pages 249-264, June.
    11. Pavel Boček & Miroslav Šiman, 2017. "On weighted and locally polynomial directional quantile regression," Computational Statistics, Springer, vol. 32(3), pages 929-946, September.
    12. Liu, Xiaohui & Zuo, Yijun & Wang, Zhizhong, 2013. "Exactly computing bivariate projection depth contours and median," Computational Statistics & Data Analysis, Elsevier, vol. 60(C), pages 1-11.
    13. Xiaohui Liu & Karl Mosler & Pavlo Mozharovskyi, 2017. "Fast computation of Tukey trimmed regions and median in dimension p > 2," Working Papers 2017-71, Center for Research in Economics and Statistics.
    14. Paindaveine, Davy & Šiman, Miroslav, 2012. "Computing multiple-output regression quantile regions," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 840-853.
    15. Daouia, Abdelaati & Paindaveine, Davy, 2019. "Multivariate Expectiles, Expectile Depth and Multiple-Output Expectile Regression," TSE Working Papers 19-1022, Toulouse School of Economics (TSE), revised Feb 2023.
    16. Merlo, Luca & Petrella, Lea & Salvati, Nicola & Tzavidis, Nikos, 2022. "Marginal M-quantile regression for multivariate dependent data," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    17. Marc Hallin & Miroslav Šiman, 2016. "Multiple-Output Quantile Regression," Working Papers ECARES ECARES 2016-03, ULB -- Universite Libre de Bruxelles.
    18. Daniel Hlubinka & Lukáš Kotík & Miroslav Šiman, 2022. "Multivariate quantiles with both overall and directional probability interpretation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(4), pages 1586-1604, December.
    19. Montes-Rojas, Gabriel, 2017. "Reduced form vector directional quantiles," Journal of Multivariate Analysis, Elsevier, vol. 158(C), pages 20-30.
    20. Paola Stolfi & Mauro Bernardi & Lea Petrella, 2018. "The sparse method of simulated quantiles: An application to portfolio optimization," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(3), pages 375-398, August.
    21. Leying Guan, 2023. "Localized conformal prediction: a generalized inference framework for conformal prediction," Biometrika, Biometrika Trust, vol. 110(1), pages 33-50.

  27. Davy Paindaveine, 2009. "On multivariate runs tests for randomness," Working Papers ECARES 2009_002, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Rainer Dyckerhoff & Christophe Ley & Davy Paindaveine, 2014. "Depth-Based Runs Tests for bivariate Central Symmetry," Working Papers ECARES ECARES 2014-03, ULB -- Universite Libre de Bruxelles.
    2. Van Bever, Germain, 2016. "Simplicial bivariate tests for randomness," Statistics & Probability Letters, Elsevier, vol. 112(C), pages 20-25.
    3. Kevin Leckey & Dennis Malcherczyk & Melanie Horn & Christine H. Müller, 2023. "Simple powerful robust tests based on sign depth," Statistical Papers, Springer, vol. 64(3), pages 857-882, June.
    4. Ludwig Baringhaus & Norbert Henze, 2016. "Revisiting the two-sample runs test," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(3), pages 432-448, September.
    5. Davy Paindaveine & Thomas Verdebout, 2013. "Universal Asymptotics for High-Dimensional Sign Tests," Working Papers ECARES ECARES 2013-40, ULB -- Universite Libre de Bruxelles.
    6. Davy Paindaveine & Julien Remy & Thomas Verdebout, 2019. "Sign Tests for Weak Principal Directions," Working Papers ECARES 2019-01, ULB -- Universite Libre de Bruxelles.

  28. Christophe Ley & Davy Paindaveine, 2009. "On the Singularity of Multivariate Skew-Symmetric Models," Working Papers ECARES 2009-017, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Dante Amengual & Xinyue Bei & Enrique Sentana, 2022. "Normal but skewed?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(7), pages 1295-1313, November.
    2. Ley, Christophe, 2023. "When the score function is the identity function - A tale of characterizations of the normal distribution," Econometrics and Statistics, Elsevier, vol. 26(C), pages 153-160.
    3. Ley, Christophe & Verdebout, Thomas, 2017. "Skew-rotationally-symmetric distributions and related efficient inferential procedures," Journal of Multivariate Analysis, Elsevier, vol. 159(C), pages 67-81.
    4. Kahrari, F. & Rezaei, M. & Yousefzadeh, F. & Arellano-Valle, R.B., 2016. "On the multivariate skew-normal-Cauchy distribution," Statistics & Probability Letters, Elsevier, vol. 117(C), pages 80-88.
    5. Christophe Ley, 2014. "Flexible Modelling in Statistics: Past, present and Future," Working Papers ECARES ECARES 2014-42, ULB -- Universite Libre de Bruxelles.
    6. Christophe Ley & Thomas Verdebout, 2014. "Skew-rotsymmetric Distributions on Unit Spheres and Related Efficient Inferential Proceedures," Working Papers ECARES ECARES 2014-46, ULB -- Universite Libre de Bruxelles.
    7. Sladana Babic & Laetitia Gelbgras & Marc Hallin & Christophe Ley, 2019. "Optimal tests for elliptical symmetry: specified and unspecified location," Working Papers ECARES 2019-26, ULB -- Universite Libre de Bruxelles.
    8. Christophe Ley & Davy Paindaveine, 2010. "On Fisher information matrices and profile log-likelihood functions in generalized skew-elliptical models," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 235-250.
    9. Yulia V. Marchenko & Marc G. Genton, 2010. "A suite of commands for fitting the skew-normal and skew-t models," Stata Journal, StataCorp LP, vol. 10(4), pages 507-539, December.
    10. Loperfido, Nicola, 2014. "Linear transformations to symmetry," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 186-192.
    11. Thomas J. DiCiccio & Anna Clara Monti, 2018. "Testing for sub-models of the skew t-distribution," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(1), pages 25-44, March.
    12. Delphine Cassart & Marc Hallin & Davy Paindaveine, 2014. "Optimal Rank Tests for Symmetry against Edgeworth-Type Alternatives," Working Papers ECARES ECARES 2014-48, ULB -- Universite Libre de Bruxelles.
    13. Ley, Christophe & Paindaveine, Davy, 2010. "Multivariate skewing mechanisms: A unified perspective based on the transformation approach," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1685-1694, December.

  29. Marc Hallin & Davy Paindaveine & Miroslav Siman, 2008. "Multivariate quantiles and multiple-output regression quantiles: from L1 optimization to halfspace depth," Working Papers ECARES 2008_042, ULB -- Universite Libre de Bruxelles.

    Cited by:

    1. Mia Hubert & Peter Rousseeuw & Pieter Segaert, 2015. "Multivariate functional outlier detection," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 177-202, July.
    2. Liu, Xiaohui & Zuo, Yijun, 2015. "CompPD: A MATLAB Package for Computing Projection Depth," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 65(i02).
    3. Davy Paindaveine & Miroslav Šiman, 2012. "Computing multiple-output regression quantile regions from projection quantiles," Computational Statistics, Springer, vol. 27(1), pages 29-49, March.
    4. Alexander, Carol & Han, Yang & Meng, Xiaochun, 2023. "Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1078-1096.
    5. Xiaohui Liu, 2017. "Fast implementation of the Tukey depth," Computational Statistics, Springer, vol. 32(4), pages 1395-1410, December.
    6. Edwin Fourrier-Nicolai & Michel Lubrano, 2021. "Bayesian Inference for Parametric Growth Incidence Curves," Working Papers halshs-03225236, HAL.
    7. Einmahl, J.H.J. & Li, Jun & Liu, Regina, 2015. "Bridging Centrality and Extremity : Refining Empirical Data Depth using Extreme Value Statistics," Other publications TiSEM bcd9783a-e07e-4da2-bc47-b, Tilburg University, School of Economics and Management.
    8. Hamel, Andreas H. & Kostner, Daniel, 2018. "Cone distribution functions and quantiles for multivariate random variables," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 97-113.
    9. Marco Alfò & Maria Francesca Marino & Maria Giovanna Ranalli & Nicola Salvati & Nikos Tzavidis, 2021. "M‐quantile regression for multivariate longitudinal data with an application to the Millennium Cohort Study," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(1), pages 122-146, January.
    10. Guillaume Carlier & Victor Chernozhukov & Alfred Galichon, 2016. "Vector Quantile Regression: An Optimal Transport Approach," Sciences Po publications info:hdl:2441/4c5431jp6o8, Sciences Po.
    11. Hemant Kulkarni & Jayabrata Biswas & Kiranmoy Das, 2019. "A joint quantile regression model for multiple longitudinal outcomes," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(4), pages 453-473, December.
    12. Pavlo Mozharovskyi & Julie Josse & François Husson, 2017. "Nonparametric imputation by data depth," Working Papers 2017-72, Center for Research in Economics and Statistics.
    13. Marc Hallin & Zudi Lu & Davy Paindaveine & Miroslav Siman, 2012. "Local Constant and Local Bilinear Multiple-Output Quantile Regression," Working Papers ECARES ECARES 2012-003, ULB -- Universite Libre de Bruxelles.
    14. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Transmission of US and EU Economic Policy Uncertainty Shock to Asian Economies in Bad and Good Times," IZA Discussion Papers 13274, Institute of Labor Economics (IZA).
    15. Guillaume Carlier & Victor Chernozhukov & Alfred Galichon, 2014. "Vector quantile regression," CeMMAP working papers 48/14, Institute for Fiscal Studies.
    16. Jean-Paul Chavas, 2018. "On multivariate quantile regression analysis," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(3), pages 365-384, August.
    17. Victor Chernozhukov & Alfred Galichon & Marc Hallin & Marc Henry, 2015. "Monge-Kantorovich Depth, Quantiles, Ranks, and Signs," Working Papers hal-03460056, HAL.
    18. Nadja Klein & Thomas Kneib, 2020. "Directional bivariate quantiles: a robust approach based on the cumulative distribution function," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(2), pages 225-260, June.
    19. María Edo & Walter Sosa Escudero & Marcela Svarc, 2021. "A multidimensional approach to measuring the middle class," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 19(1), pages 139-162, March.
    20. Zuo, Yijun, 2013. "Multidimensional medians and uniqueness," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 82-88.
    21. Hallin, Marc & Šiman, Miroslav, 2016. "Elliptical multiple-output quantile regression and convex optimization," Statistics & Probability Letters, Elsevier, vol. 109(C), pages 232-237.
    22. Paola Stolfi & Mauro Bernardi & Lea Petrella, 2016. "Multivariate Method Of Simulated Quantiles," Departmental Working Papers of Economics - University 'Roma Tre' 0212, Department of Economics - University Roma Tre.
    23. Yi He & John H. J. Einmahl, 2017. "Estimation of extreme depth-based quantile regions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(2), pages 449-461, March.
    24. Hlubinka, Daniel & Šiman, Miroslav, 2013. "On elliptical quantiles in the quantile regression setup," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 163-171.
    25. Ochoa Arellano, Maicol Jesús & Cascos Fernández, Ignacio, 2022. "Data depth and multiple output regression, the distorted M-quantiles approach," DES - Working Papers. Statistics and Econometrics. WS 35465, Universidad Carlos III de Madrid. Departamento de Estadística.
    26. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
    27. Daniel Hlubinka & Miroslav Šiman, 2015. "On generalized elliptical quantiles in the nonlinear quantile regression setup," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(2), pages 249-264, June.
    28. Davy Paindaveine & Miroslav Siman, 2009. "On directional multiple-output quantile regression," Working Papers ECARES 2009_011, ULB -- Universite Libre de Bruxelles.
    29. Holger Dette & Stefan Hoderlein & Natalie Neumeyer, 2013. "Testing Multivariate Economic Restrictions Using Quantiles: The Example of Slutsky Negative Semidefiniteness," Boston College Working Papers in Economics 836, Boston College Department of Economics.
    30. Torres Díaz, Raúl Andrés & Michele, Carlo de & Lillo Rodríguez, Rosa Elvira & Laniado Rodas, Henry, 2016. "Directional multivariate extremes in environmental phenomena," DES - Working Papers. Statistics and Econometrics. WS 23419, Universidad Carlos III de Madrid. Departamento de Estadística.
    31. Sarno, Lucio & Schneider, Paul & Wagner, Christian, 2011. "Properties of Foreign Exchange Risk Premiums," CEPR Discussion Papers 8503, C.E.P.R. Discussion Papers.
    32. Gneiting, Tilmann, 2011. "Making and Evaluating Point Forecasts," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 746-762.
    33. Pavel Boček & Miroslav Šiman, 2017. "On weighted and locally polynomial directional quantile regression," Computational Statistics, Springer, vol. 32(3), pages 929-946, September.
    34. Petrella, Lea & Raponi, Valentina, 2019. "Joint estimation of conditional quantiles in multivariate linear regression models with an application to financial distress," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 70-84.
    35. Liqun Yu & Nan Lin, 2017. "ADMM for Penalized Quantile Regression in Big Data," International Statistical Review, International Statistical Institute, vol. 85(3), pages 494-518, December.
    36. Bazovkin, Pavel & Mosler, Karl, 2012. "An Exact Algorithm for Weighted-Mean Trimmed Regions in Any Dimension," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 47(i13).
    37. Kotík, Lukáš & Hlubinka, Daniel, 2017. "A weighted localization of halfspace depth and its properties," Journal of Multivariate Analysis, Elsevier, vol. 157(C), pages 53-69.
    38. Bhattacharya, Indrabati & Ghosal, Subhashis, 2021. "Bayesian multivariate quantile regression using Dependent Dirichlet Process prior," Journal of Multivariate Analysis, Elsevier, vol. 185(C).
    39. Xiaochun Meng & James W. Taylor & Souhaib Ben Taieb & Siran Li, 2020. "Scores for Multivariate Distributions and Level Sets," Papers 2002.09578, arXiv.org, revised Jun 2023.
    40. Xiaohui Liu & Karl Mosler & Pavlo Mozharovskyi, 2017. "Fast computation of Tukey trimmed regions and median in dimension p > 2," Working Papers 2017-71, Center for Research in Economics and Statistics.
    41. Christophe Ley & Camille Sabbah & Thomas Verdebout, 2014. "A new concept of quantiles for directional data and the angular Mahalanobis depth," Working Papers ECARES ECARES 2013-23, ULB -- Universite Libre de Bruxelles.
    42. Maria Marino & Alessio Farcomeni, 2015. "Linear quantile regression models for longitudinal experiments: an overview," METRON, Springer;Sapienza Università di Roma, vol. 73(2), pages 229-247, August.
    43. Paindaveine, Davy & Šiman, Miroslav, 2012. "Computing multiple-output regression quantile regions," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 840-853.
    44. Roger Koenker, 2017. "Quantile regression 40 years on," CeMMAP working papers CWP36/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    45. Isabelle Charlier & Davy Paindaveine & Jérôme Saracco, 2016. "Multiple-Output Quantile Regression through Optimal Quantization," Working Papers ECARES ECARES 2016-18, ULB -- Universite Libre de Bruxelles.
    46. Ra'ul Torres & Rosa E. Lillo & Henry Laniado, 2015. "A Directional Multivariate Value at Risk," Papers 1502.00908, arXiv.org.
    47. Nadja Klein & Torsten Hothorn & Luisa Barbanti & Thomas Kneib, 2022. "Multivariate conditional transformation models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(1), pages 116-142, March.
    48. Davy Paindaveine & Germain Van Bever, 2017. "Halfspace Depths for Scatter, Concentration and Shape Matrices," Working Papers ECARES ECARES 2017-19, ULB -- Universite Libre de Bruxelles.
    49. Klaus Herrmann & Marius Hofert & Melina Mailhot, 2017. "Multivariate Geometric Expectiles," Papers 1704.01503, arXiv.org, revised Jan 2018.
    50. Roger Koenker, 2017. "Quantile regression 40 years on," CeMMAP working papers 36/17, Institute for Fiscal Studies.
    51. Daouia, Abdelaati & Paindaveine, Davy, 2019. "Multivariate Expectiles, Expectile Depth and Multiple-Output Expectile Regression," TSE Working Papers 19-1022, Toulouse School of Economics (TSE), revised Feb 2023.
    52. Bernardi, Mauro & Bottone, Marco & Petrella, Lea, 2018. "Bayesian quantile regression using the skew exponential power distribution," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 92-111.
    53. Osipenko, Maria, 2021. "Directional assessment of traffic flow extremes," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 353-369.
    54. Dyckerhoff, Rainer & Mozharovskyi, Pavlo, 2016. "Exact computation of the halfspace depth," Computational Statistics & Data Analysis, Elsevier, vol. 98(C), pages 19-30.
    55. L. Jeff Hong & Zhiyuan Huang & Henry Lam, 2021. "Learning-Based Robust Optimization: Procedures and Statistical Guarantees," Management Science, INFORMS, vol. 67(6), pages 3447-3467, June.
    56. Maicol Ochoa & Ignacio Cascos, 2022. "Data Depth and Multiple Output Regression, the Distorted M -Quantiles Approach," Mathematics, MDPI, vol. 10(18), pages 1-19, September.
    57. Yves Dominicy & Pauliina Ilmonen & David Veredas, 2017. "Multivariate Hill Estimators," International Statistical Review, International Statistical Institute, vol. 85(1), pages 108-142, April.
    58. Kneib, Thomas & Silbersdorff, Alexander & Säfken, Benjamin, 2023. "Rage Against the Mean – A Review of Distributional Regression Approaches," Econometrics and Statistics, Elsevier, vol. 26(C), pages 99-123.
    59. Davy Paindaveine & Germain Van Bever, 2017. "Tyler Shape Depth," Working Papers ECARES ECARES 2017-29, ULB -- Universite Libre de Bruxelles.
    60. Fraiman, Ricardo & Pateiro-López, Beatriz, 2012. "Quantiles for finite and infinite dimensional data," Journal of Multivariate Analysis, Elsevier, vol. 108(C), pages 1-14.
    61. Agarwal, Gaurav & Tu, Wei & Sun, Ying & Kong, Linglong, 2022. "Flexible quantile contour estimation for multivariate functional data: Beyond convexity," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
    62. Torres, Raúl & Lillo, Rosa E. & Laniado, Henry, 2015. "A directional multivariate value at risk," Insurance: Mathematics and Economics, Elsevier, vol. 65(C), pages 111-123.
    63. Merlo, Luca & Petrella, Lea & Salvati, Nicola & Tzavidis, Nikos, 2022. "Marginal M-quantile regression for multivariate dependent data," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    64. Shih-Kang Chao & Wolfgang K. Härdle & Ming Yuan, 2015. "Factorisable Sparse Tail Event Curves," SFB 649 Discussion Papers SFB649DP2015-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    65. Daniel Hlubinka & Lukáš Kotík & Miroslav Šiman, 2022. "Multivariate quantiles with both overall and directional probability interpretation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(4), pages 1586-1604, December.
    66. Davy Paindaveine & Germain Van Bever, 2015. "Discussion of “Multivariate Functional Outlier Detection”, by Mia Hubert, Peter Rousseeuw and Pieter Segaert," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 223-231, July.
    67. Feng, Xiang-Nan & Wang, Yifan & Lu, Bin & Song, Xin-Yuan, 2017. "Bayesian regularized quantile structural equation models," Journal of Multivariate Analysis, Elsevier, vol. 154(C), pages 234-248.
    68. Mia Hubert & Peter Rousseeuw & Pieter Segaert, 2017. "Multivariate and functional classification using depth and distance," 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(3), pages 445-466, September.
    69. Feng, Sanying & Lian, Heng & Zhu, Fukang, 2016. "Reduced rank regression with possibly non-smooth criterion functions: An empirical likelihood approach," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 139-150.
    70. Luca Merlo & Lea Petrella & Nikos Tzavidis, 2022. "Quantile mixed hidden Markov models for multivariate longitudinal data: An application to children's Strengths and Difficulties Questionnaire scores," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(2), pages 417-448, March.
    71. Montes-Rojas, Gabriel, 2017. "Reduced form vector directional quantiles," Journal of Multivariate Analysis, Elsevier, vol. 158(C), pages 20-30.
    72. Sulkhan Chavleishvili & Simone Manganelli, 2024. "Forecasting and stress testing with quantile vector autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 66-85, January.
    73. Paola Stolfi & Mauro Bernardi & Lea Petrella, 2018. "The sparse method of simulated quantiles: An application to portfolio optimization," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(3), pages 375-398, August.
    74. Christian Francq & Jean-Michel Zakoïan, 2020. "Adaptiveness of the empirical distribution of residuals in semi- parametric conditional location scale models," Working Papers hal-02898909, HAL.
    75. Carlier, Guillaume & Chernozhukov, Victor & Galichon, Alfred, 2017. "Vector quantile regression beyond the specified case," Journal of Multivariate Analysis, Elsevier, vol. 161(C), pages 96-102.
    76. Laketa, Petra & Nagy, Stanislav, 2021. "Reconstruction of atomic measures from their halfspace depth," Journal of Multivariate Analysis, Elsevier, vol. 183(C).
    77. Jayabrata Biswas & Kiranmoy Das, 2021. "A Bayesian quantile regression approach to multivariate semi-continuous longitudinal data," Computational Statistics, Springer, vol. 36(1), pages 241-260, March.

  30. Allal, Jelloul & Kaaouachi, Abdelali & Paindaveine, Davy, 2001. "R-estimation for ARMA models," MPRA Paper 21167, University Library of Munich, Germany.

    Cited by:

    1. Hallin, Marc & La Vecchia, Davide, 2017. "R-estimation in semiparametric dynamic location-scale models," Journal of Econometrics, Elsevier, vol. 196(2), pages 233-247.
    2. Hallin, Marc & Swan, Yvik & Verdebout, Thomas & Veredas, David, 2013. "One-step R-estimation in linear models with stable errors," Journal of Econometrics, Elsevier, vol. 172(2), pages 195-204.

  31. Bruss, F. Thomas & Paindaveine, Davy, 2000. "Selecting a sequence of last successes in independent trials," MPRA Paper 21166, University Library of Munich, Germany.

    Cited by:

    1. Dendievel, Rémi, 2015. "Weber’s optimal stopping problem and generalizations," Statistics & Probability Letters, Elsevier, vol. 97(C), pages 176-184.
    2. Gnedin, A.V.Alexander V., 2004. "Best choice from the planar Poisson process," Stochastic Processes and their Applications, Elsevier, vol. 111(2), pages 317-354, June.

Articles

  1. Paindaveine, Davy & Siman, Miroslav, 2011. "On directional multiple-output quantile regression," Journal of Multivariate Analysis, Elsevier, vol. 102(2), pages 193-212, February.
    See citations under working paper version above.
  2. Christophe Ley & Davy Paindaveine, 2010. "On Fisher information matrices and profile log-likelihood functions in generalized skew-elliptical models," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 235-250.

    Cited by:

    1. Christophe Ley & Anouk Neven, 2013. "Simple Le Cam Optimal Inference for the Tail Weight of Multivariate Student t Distributions: Testing Procedures and Estimation," Working Papers ECARES ECARES 2013-26, ULB -- Universite Libre de Bruxelles.
    2. Wang, Sheng & Zimmerman, Dale L. & Breheny, Patrick, 2020. "Sparsity-regularized skewness estimation for the multivariate skew normal and multivariate skew t distributions," Journal of Multivariate Analysis, Elsevier, vol. 179(C).
    3. Kahrari, F. & Rezaei, M. & Yousefzadeh, F. & Arellano-Valle, R.B., 2016. "On the multivariate skew-normal-Cauchy distribution," Statistics & Probability Letters, Elsevier, vol. 117(C), pages 80-88.
    4. Christophe Ley, 2014. "Flexible Modelling in Statistics: Past, present and Future," Working Papers ECARES ECARES 2014-42, ULB -- Universite Libre de Bruxelles.
    5. Loperfido, Nicola, 2014. "Linear transformations to symmetry," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 186-192.
    6. Thomas J. DiCiccio & Anna Clara Monti, 2018. "Testing for sub-models of the skew t-distribution," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(1), pages 25-44, March.
    7. Arellano-Valle, Reinaldo B. & Azzalini, Adelchi, 2013. "The centred parameterization and related quantities of the skew-t distribution," Journal of Multivariate Analysis, Elsevier, vol. 113(C), pages 73-90.

  3. Ley, Christophe & Paindaveine, Davy, 2010. "On the singularity of multivariate skew-symmetric models," Journal of Multivariate Analysis, Elsevier, vol. 101(6), pages 1434-1444, July.
    See citations under working paper version above.
  4. Ley, Christophe & Paindaveine, Davy, 2010. "Multivariate skewing mechanisms: A unified perspective based on the transformation approach," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1685-1694, December.

    Cited by:

    1. Félix Belzunce & Julio Mulero & José María Ruíz & Alfonso Suárez-Llorens, 2015. "On relative skewness for multivariate distributions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(4), pages 813-834, December.
    2. Christophe Ley, 2014. "Flexible Modelling in Statistics: Past, present and Future," Working Papers ECARES ECARES 2014-42, ULB -- Universite Libre de Bruxelles.
    3. Rubio, Francisco Javier & Steel, Mark F. J., 2014. "Bayesian modelling of skewness and kurtosis with two-piece scale and shape transformations," MPRA Paper 57102, University Library of Munich, Germany.
    4. Manuela Braione & Nicolas K. Scholtes, 2016. "Forecasting Value-at-Risk under Different Distributional Assumptions," Econometrics, MDPI, vol. 4(1), pages 1-27, January.
    5. Baillien, Jonas & Gijbels, Irène & Verhasselt, Anneleen, 2023. "A new distance based measure of asymmetry," Journal of Multivariate Analysis, Elsevier, vol. 193(C).
    6. Lee, Sharon X. & McLachlan, Geoffrey J., 2022. "An overview of skew distributions in model-based clustering," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    7. Jupp, P.E. & Regoli, G. & Azzalini, A., 2016. "A general setting for symmetric distributions and their relationship to general distributions," Journal of Multivariate Analysis, Elsevier, vol. 148(C), pages 107-119.
    8. M. C. Jones, 2015. "On Families of Distributions with Shape Parameters," International Statistical Review, International Statistical Institute, vol. 83(2), pages 175-192, August.
    9. Gurjeet Dhesi & Bilal Shakeel & Marcel Ausloos, 2021. "Modelling and forecasting the kurtosis and returns distributions of financial markets: irrational fractional Brownian motion model approach," Annals of Operations Research, Springer, vol. 299(1), pages 1397-1410, April.
    10. Jonas Baillien & Irène Gijbels & Anneleen Verhasselt, 2023. "Flexible asymmetric multivariate distributions based on two-piece univariate distributions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(1), pages 159-200, February.

  5. Paindaveine, Davy, 2009. "On Multivariate Runs Tests for Randomness," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1525-1538.
    See citations under working paper version above.
  6. Hallin, Marc & Paindaveine, Davy, 2009. "Optimal tests for homogeneity of covariance, scale, and shape," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 422-444, March.

    Cited by:

    1. Stephanie Aerts & Gentiane Haesbroeck, 2017. "Robust asymptotic tests for the equality of multivariate coefficients of variation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(1), pages 163-187, March.
    2. Frahm, Gabriel, 2009. "Asymptotic distributions of robust shape matrices and scales," Journal of Multivariate Analysis, Elsevier, vol. 100(7), pages 1329-1337, August.
    3. Marc Hallin & Davy Paindaveine & Thomas Verdebout, 2009. "Optimal rank-based testing for principal component," Working Papers ECARES 2009_013, ULB -- Universite Libre de Bruxelles.
    4. Marc Hallin, 2008. "On the Non Gaussian Asymptotics of the Likelihood Ratio Test Statistic for Homogeneity of Covariance," Working Papers ECARES 2008_039, ULB -- Universite Libre de Bruxelles.
    5. Sladana Babic & Laetitia Gelbgras & Marc Hallin & Christophe Ley, 2019. "Optimal tests for elliptical symmetry: specified and unspecified location," Working Papers ECARES 2019-26, ULB -- Universite Libre de Bruxelles.
    6. Davy Paindaveine & Joséa Rasoafaraniaina & Thomas Verdebout, 2021. "Preliminary test estimation in uniformly locally asymptotically normal models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 689-707, June.
    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.
    8. Marc Hallin & Davy Paindaveine & Thomas Verdebout, 2011. "Optimal Rank-Based Tests for Common Principal Components," Working Papers ECARES ECARES 2011-032, ULB -- Universite Libre de Bruxelles.

  7. Nordhausen, Klaus & Oja, Hannu & Paindaveine, Davy, 2009. "Signed-rank tests for location in the symmetric independent component model," Journal of Multivariate Analysis, Elsevier, vol. 100(5), pages 821-834, May.

    Cited by:

    1. Hannu Oja & Davy Paindaveine & Sara Taskinen, 2009. "Parametric and nonparametric test for multivariate independence in IC models," Working Papers ECARES 2009_018, ULB -- Universite Libre de Bruxelles.
    2. Ilmonen, Pauliina & Nevalainen, Jaakko & Oja, Hannu, 2010. "Characteristics of multivariate distributions and the invariant coordinate system," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1844-1853, December.
    3. Bagkavos, Dimitrios & Patil, Prakash N., 2021. "Improving the Wilcoxon signed rank test by a kernel smooth probability integral transformation," Statistics & Probability Letters, Elsevier, vol. 171(C).
    4. Davy Paindaveine & Germain Van Bever, 2017. "Halfspace Depths for Scatter, Concentration and Shape Matrices," Working Papers ECARES ECARES 2017-19, ULB -- Universite Libre de Bruxelles.
    5. David E. Tyler & Frank Critchley & Lutz Dümbgen & Hannu Oja, 2009. "Invariant co‐ordinate selection," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(3), pages 549-592, June.

  8. Paindaveine, Davy, 2008. "A canonical definition of shape," Statistics & Probability Letters, Elsevier, vol. 78(14), pages 2240-2247, October.

    Cited by:

    1. Frahm, Gabriel & Jaekel, Uwe, 2010. "A generalization of Tyler's M-estimators to the case of incomplete data," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 374-393, February.
    2. Hallin, Marc & Šiman, Miroslav, 2016. "Elliptical multiple-output quantile regression and convex optimization," Statistics & Probability Letters, Elsevier, vol. 109(C), pages 232-237.
    3. Frahm, Gabriel, 2009. "Asymptotic distributions of robust shape matrices and scales," Journal of Multivariate Analysis, Elsevier, vol. 100(7), pages 1329-1337, August.
    4. Dürre, Alexander & Vogel, Daniel & Fried, Roland, 2015. "Spatial sign correlation," Journal of Multivariate Analysis, Elsevier, vol. 135(C), pages 89-105.
    5. Paindaveine, Davy & Van Bever, Germain, 2014. "Inference on the shape of elliptical distributions based on the MCD," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 125-144.
    6. Marc Hallin & Davy Paindaveine & Thomas Verdebout, 2009. "Optimal rank-based testing for principal component," Working Papers ECARES 2009_013, ULB -- Universite Libre de Bruxelles.
    7. Marc Hallin, 2008. "On the Non Gaussian Asymptotics of the Likelihood Ratio Test Statistic for Homogeneity of Covariance," Working Papers ECARES 2008_039, ULB -- Universite Libre de Bruxelles.
    8. Davy Paindaveine & Germain Van Bever, 2013. "Inference on the Shape of Elliptical Distribution Based on the MCD," Working Papers ECARES ECARES 2013-27, ULB -- Universite Libre de Bruxelles.
    9. Xin Dang & Hailin Sang & Lauren Weatherall, 2019. "Gini covariance matrix and its affine equivariant version," Statistical Papers, Springer, vol. 60(3), pages 641-666, June.
    10. Christophe Ley & Davy Paindaveine, 2010. "On Fisher information matrices and profile log-likelihood functions in generalized skew-elliptical models," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 235-250.
    11. Dürre, Alexander & Vogel, Daniel, 2016. "Asymptotics of the two-stage spatial sign correlation," Journal of Multivariate Analysis, Elsevier, vol. 144(C), pages 54-67.
    12. Hallin Marc & Paindaveine Davy, 2006. "Parametric and semiparametric inference for shape: the role of the scale functional," Statistics & Risk Modeling, De Gruyter, vol. 24(3), pages 1-24, December.
    13. Frahm, Gabriel & Nordhausen, Klaus & Oja, Hannu, 2020. "M-estimation with incomplete and dependent multivariate data," Journal of Multivariate Analysis, Elsevier, vol. 176(C).
    14. Yves Dominicy & Pauliina Ilmonen & David Veredas, 2017. "Multivariate Hill Estimators," International Statistical Review, International Statistical Institute, vol. 85(1), pages 108-142, April.
    15. Taskinen, Sara & Koch, Inge & Oja, Hannu, 2012. "Robustifying principal component analysis with spatial sign vectors," Statistics & Probability Letters, Elsevier, vol. 82(4), pages 765-774.
    16. Davy Paindaveine & Germain Van Bever, 2017. "Tyler Shape Depth," Working Papers ECARES ECARES 2017-29, ULB -- Universite Libre de Bruxelles.
    17. Dürre, Alexander & Tyler, David E. & Vogel, Daniel, 2016. "On the eigenvalues of the spatial sign covariance matrix in more than two dimensions," Statistics & Probability Letters, Elsevier, vol. 111(C), pages 80-85.
    18. Marc Hallin & Davy Paindaveine & Thomas Verdebout, 2013. "Efficient R-Estimation of Principal and Common Principal Components," Working Papers ECARES ECARES 2013-18, ULB -- Universite Libre de Bruxelles.
    19. Croux, C. & Dehon, C. & Yadine, A., 2010. "The K-Step Spatial Sign Covariance Matrix," Other publications TiSEM b3c069e5-3f34-475a-9c1b-1, Tilburg University, School of Economics and Management.
    20. Eduardo Garcia-Portugues & Davy Paindaveine & Thomas Verdebout, 2020. "On optimal tests for rotational symmetry against new classes of hyperspherical distributions," Post-Print hal-03169388, HAL.
    21. Marc Hallin & Miroslav Šiman, 2016. "Multiple-Output Quantile Regression," Working Papers ECARES ECARES 2016-03, ULB -- Universite Libre de Bruxelles.
    22. Seija Sirkiä & Sara Taskinen & Hannu Oja & David Tyler, 2009. "Tests and estimates of shape based on spatial signs and ranks," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(2), pages 155-176.
    23. Marc Hallin & Davy Paindaveine & Thomas Verdebout, 2011. "Optimal Rank-Based Tests for Common Principal Components," Working Papers ECARES ECARES 2011-032, ULB -- Universite Libre de Bruxelles.

  9. Paindaveine, Davy, 2006. "A Chernoff-Savage result for shape:On the non-admissibility of pseudo-Gaussian methods," Journal of Multivariate Analysis, Elsevier, vol. 97(10), pages 2206-2220, November.

    Cited by:

    1. Marc Hallin & Davy Paindaveine & Thomas Verdebout, 2009. "Optimal rank-based testing for principal component," Working Papers ECARES 2009_013, ULB -- Universite Libre de Bruxelles.
    2. Marc Hallin & Davy Paindaveine & Thomas Verdebout, 2013. "Efficient R-Estimation of Principal and Common Principal Components," Working Papers ECARES ECARES 2013-18, ULB -- Universite Libre de Bruxelles.
    3. Davy Paindaveine & Thomas Verdebout, 2011. "Rank Tests for Elliptical Graphical Modeling," Working Papers ECARES ECARES 2011-039, ULB -- Universite Libre de Bruxelles.
    4. Marc Hallin & Davy Paindaveine & Thomas Verdebout, 2011. "Optimal Rank-Based Tests for Common Principal Components," Working Papers ECARES ECARES 2011-032, ULB -- Universite Libre de Bruxelles.

  10. Hallin, Marc & Paindaveine, Davy, 2005. "Affine-invariant aligned rank tests for the multivariate general linear model with VARMA errors," Journal of Multivariate Analysis, Elsevier, vol. 93(1), pages 122-163, March.

    Cited by:

    1. Marc Hallin & Ramon van den Akker & Bas Werker, 2012. "Rank-Based Tests of the Cointegrating Rank in Semiparametric Error Correction Models," Working Papers ECARES ECARES 2012-042, ULB -- Universite Libre de Bruxelles.
    2. Hallin, Marc & La Vecchia, Davide, 2020. "A Simple R-estimation method for semiparametric duration models," Journal of Econometrics, Elsevier, vol. 218(2), pages 736-749.
    3. Paindaveine, Davy, 2006. "A Chernoff-Savage result for shape:On the non-admissibility of pseudo-Gaussian methods," Journal of Multivariate Analysis, Elsevier, vol. 97(10), pages 2206-2220, November.
    4. Victor Chernozhukov & Alfred Galichon & Marc Hallin & Marc Henry, 2015. "Monge-Kantorovich Depth, Quantiles, Ranks, and Signs," Working Papers hal-03460056, HAL.
    5. Bramati, Maria Caterina, 2013. "Optimal rank-based tests for block exogeneity in vector autoregressions," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 141-162.
    6. Hallin, M. & Werker, B.J.M. & van den Akker, R., 2015. "Optimal Pseudo-Gaussian and Rank-based Tests of the Cointegration Rank in Semiparametric Error-correction Models," Discussion Paper 2015-001, Tilburg University, Center for Economic Research.
    7. Marc Hallin & Davy Paindaveine & Thomas Verdebout, 2009. "Optimal rank-based testing for principal component," Working Papers ECARES 2009_013, ULB -- Universite Libre de Bruxelles.
    8. Marc Hallin & Yvik Swan & Thomas Verdebout, 2013. "A Serial Version of Hodges and Lehmann's "6/pi Result"," Working Papers ECARES ECARES 2013-17, ULB -- Universite Libre de Bruxelles.
    9. Serfling, Robert & Wang, Yunfei, 2016. "On Liu’s simplicial depth and Randles’ interdirections," Computational Statistics & Data Analysis, Elsevier, vol. 99(C), pages 235-247.
    10. Sladana Babic & Laetitia Gelbgras & Marc Hallin & Christophe Ley, 2019. "Optimal tests for elliptical symmetry: specified and unspecified location," Working Papers ECARES 2019-26, ULB -- Universite Libre de Bruxelles.
    11. Francq, C. & Jiménez-Gamero, M.D. & Meintanis, S.G., 2017. "Tests for conditional ellipticity in multivariate GARCH models," Journal of Econometrics, Elsevier, vol. 196(2), pages 305-319.
    12. Paindaveine, Davy, 2009. "On Multivariate Runs Tests for Randomness," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1525-1538.
    13. Hallin, Marc & van den Akker, Ramon & Werker, Bas J.M., 2016. "Semiparametric error-correction models for cointegration with trends: Pseudo-Gaussian and optimal rank-based tests of the cointegration rank," Journal of Econometrics, Elsevier, vol. 190(1), pages 46-61.

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