D. Paindaveine

发表

Semiparametrically efficient inference based on signed ranks in symmetric independent component models

Pauliina Ilmonen, D. Paindaveine, 2011, 1202.5159.

MINIMAX ESTIMATION OF LINEAR AND QUADRATIC FUNCTIONALS ON SPARSITY CLASSES

N. Wermuth, S. Lauritzen, Taiji Suzuki, 2017 .

Efficient R-Estimation of Principal and Common Principal Components

D. Paindaveine, M. Hallin, Thomas Verdebout, 2014 .

On Fisher information matrices and profile log-likelihood functions in generalized skew-elliptical models

Christophe Ley, D. Paindaveine, 2010 .

Sign tests for weak principal directions

D. Paindaveine, Thomas Verdebout, Julien Remy, 2018, Bernoulli.

On the power of axial tests of uniformity on spheres

D. Paindaveine, Thomas Verdebout, C. Cutting, 2019, 1910.09391.

On Optimal Tests for Rotational Symmetry Against New Classes of Hyperspherical Distributions

D. Paindaveine, Thomas Verdebout, E. García-Portugués, 2017, Journal of the American Statistical Association.

SEMIPARAMETRICALLY EFFICIENT RANK-BASED INFERENCE FOR SHAPE I. OPTIMAL RANK-BASED TESTS FOR SPHERICITY

D. Paindaveine, M. Hallin, 2006, 0707.4621.

SEMIPARAMETRICALLY EFFICIENT RANK-BASED INFERENCE FOR SHAPE II. OPTIMAL R-ESTIMATION OF SHAPE

D. Paindaveine, H. Oja, M. Hallin, 2006, 0708.0079.

Halfspace depths for scatter, concentration and shape matrices

Germain Van Bever, D. Paindaveine, 2017, The Annals of Statistics.

Tyler shape depth

Germain Van Bever, D. Paindaveine, 2017, Biometrika.

From Halfspace M-Depth to Multiple-output Expectile Regression

D. Paindaveine, Abdelaati Daouia, A. Daouia, 2019, 1905.12718.

Multivariate quantiles and multiple-output regression quantiles: from L1 optimization to halfspace depth

D. Paindaveine, M. Hallin, Miroslav vSiman, 2010, 1002.4486.

Nonparametrically consistent depth-based classifiers

Germain Van Bever, D. Paindaveine, 2012, 1204.2996.

From Depth to Local Depth: A Focus on Centrality

D. Paindaveine, Germain Van bever, 2013 .

ST ] 3 0 N ov 2 01 8 Tyler Shape Depth

Germain Van Bever, D. Paindaveine, 2018 .

Contributions to nonparametric and semiparametric inference based on statistical depth

Germain Van Bever, D. Paindaveine, 2013 .

Optimal tests for multivariate location based on interdirections and pseudo-Mahalanobis ranks

D. Paindaveine, M. Hallin, 2002 .

Optimal procedures based on interdirections and pseudo-Mahalanobis ranks for testing multivariate elliptic white noise against ARMA dependence

D. Paindaveine, M. Hallin, 2002 .

Multivariate signed ranks: Randles' interdirections or Tyler's angles?

D. Paindaveine, M. Hallin, 2002 .

Affine-invariant rank tests for multivariate independence in independent component models

D. Paindaveine, H. Oja, S. Taskinen, 2016 .

Elliptical Symmetry

D. Paindaveine, 2022 .

Depth-based runs tests for bivariate central symmetry

Christophe Ley, Davy Paindaveine, Rainer Dyckerhoff, 2012 .

A canonical definition of shape

Davy Paindaveine, D. Paindaveine, 2008 .

On High-Dimensional Sign Tests

Thomas Verdebout, Davy Paindaveine, D. Paindaveine, 2016 .

Probit Transformation for Nonparametric Kernel Estimation of the Copula Density

Arthur Charpentier, Gery Geenens, Davy Paindaveine, 2014, 1404.4414.

Optimal rank-based tests for common principal components

D. Paindaveine, M. Hallin, Thomas Verdebout, 2013 .

Testing uniformity on high-dimensional spheres against monotone rotationally symmetric alternatives

D. Paindaveine, Thomas Verdebout, C. Cutting, 2015, 1502.02120.

Tests of Concentration for Low-Dimensional and High-Dimensional Directional Data

Thomas Verdebout, Davy Paindaveine, D. Paindaveine, 2017 .

Multiple‐output quantile regression through optimal quantization

D. Paindaveine, J. Saracco, Isabelle Charlier, 2019, Scandinavian Journal of Statistics.

Conditional quantile estimation through optimal quantization

D. Paindaveine, J. Saracco, Isabelle Charlier, 2014, 1405.2781.

On Multivariate Runs Tests for Randomness

D. Paindaveine, 2009 .

On Multivariate Runs Tests for Randomness Davy Paindaveine

D. Paindaveine, 2009 .

Universal Asymptotics for High-Dimensional Sign Tests

D. Paindaveine, Thomas Verdebout, 2013 .

RESEARCH ARTICLE Testing for Common Principal Components under Heterokurticity

D. Paindaveine, M. Hallin, Thomas Verdebout, 2010 .

Testing for Common Principal Components under Heterokurticity

D. Paindaveine, M. Hallin, Thomas Verdebout, 2010 .

Local bilinear multiple-output quantile/depth regression

D. Paindaveine, M. Hallin, Zudi Lu, 2015, 1507.07754.

Detecting the direction of a signal on high-dimensional spheres: non-null and Le Cam optimality results

D. Paindaveine, Thomas Verdebout, 2017, Probability Theory and Related Fields.

Preliminary test estimation in ULAN models

D. Paindaveine, Thomas Verdebout, Joséa Rasoafaraniaina, 2019, 1906.10967.

Testing for principal component directions under weak identifiability

D. Paindaveine, Thomas Verdebout, Julien Remy, 2017, The Annals of Statistics.

Rejoinder to "Multivariate quantiles and multiple-output regression quantiles: From $L_1$ optimization to halfspace depth"

D. Paindaveine, M. Hallin, Miroslav vSiman, 2010, 1002.4515.

On High-Dimensional Sign Tests

D. Paindaveine, Thomas Verdebout, 2013, 1311.3118.

de la Société Française de Statistique Rank Tests for Elliptical Graphical Modeling Titre : Tests

D. Paindaveine, Thomas Verdebout, 2011 .

DISCOVER WILEY'S LEADING STATISTICS JOURNALS

Concha Bielza, Pedro Larrañaga, Serge Rudaz, 2014 .

Rank-based optimal tests of the adequacy of an elliptic VARMA model

D. Paindaveine, M. Hallin, 2004, math/0508603.

Parametric and non ‐ Parametric Test for Multivariate Independence in

D. Paindaveine, H. Oja, S. Taskinen, 2009 .

Multivariate skewing mechanisms: A unified perspective based on the transformation approach

Christophe Ley, D. Paindaveine, 2010 .

Revisiting the name variant of the two-children problem

D. Paindaveine, P. Spindel, 2022, 2205.12804.

Local constant and local bilinear multiple-output quantile regression

D. Paindaveine, M. Hallin, M. Siman, 2012 .

SFB 823 Local constant and local bilinear multiple-output quantile regression D iscussion P aper

D. Paindaveine, M. Hallin, M. Siman, 2012 .

Affine-equivariant inference for multivariate location under Lp loss functions

D. Paindaveine, A. Dürre, 2022, The Annals of Statistics.

Detecting the direction of a signal on high-dimensional spheres: non-null and Le Cam optimality results

D. Paindaveine, Thomas Verdebout, 2019, Probability Theory and Related Fields.

Depth-based runs tests for bivariate central symmetry

Christophe Ley, D. Paindaveine, R. Dyckerhoff, 2014, 1401.2377.

Computing multiple-output regression quantile regions from projection quantiles

D. Paindaveine, M. Siman, 2011, Computational Statistics.

Optimal Rank-Based Tests for the Location Parameter of a Rotationally Symmetric Distribution on the Hypersphere

D. Paindaveine, Thomas Verdebout, 2015 .

Optimal Rank-based Tests for Sphericity

D. Paindaveine, 2005 .

Local asymptotic normality property for lacunar wavelet series multifractal model

Jean-Michel Loubes, D. Paindaveine, 2011 .

Optimal Rank Tests for Symmetry against Edgeworth-Type Alternatives

D. Paindaveine, M. Hallin, D. Cassart, 2015 .

Runs Test: Theory

Christophe Ley, D. Paindaveine, 2014 .

Univariate and multivariate symmetry: statistical inference and distributional aspects

Christophe Ley, Davy Paindaveine, Christophe Ley, 2010 .

Inference on the shape of elliptical distributions based on the MCD

Germain Van Bever, Davy Paindaveine, D. Paindaveine, 2014, J. Multivar. Anal..

OPTIMAL RANK-BASED TESTING FOR PRINCIPAL COMPONENTS

Thomas Verdebout, Marc Hallin, Davy Paindaveine, 2010, 1211.2117.

Optimal tests for homogeneity of covariance, scale, and shape

Marc Hallin, Davy Paindaveine, D. Paindaveine, 2009, J. Multivar. Anal..

Inference for spherical location under high concentration

D. Paindaveine, Thomas Verdebout, 2019, The Annals of Statistics.

Inference on the mode of weak directional signals: a Le Cam perspective on hypothesis testing near singularities

D. Paindaveine, Thomas Verdebout, 2015, 1512.04594.

High-dimensional tests for spherical location and spiked covariance

Thomas Verdebout, Christophe Ley, Davy Paindaveine, 2014, J. Multivar. Anal..

On the power of Sobolev tests for isotropy under local rotationally symmetric alternatives

Thomas Verdebout, Eduardo Garc'ia-Portugu'es, Davy Paindaveine, 2021, 2108.09874.

Pseudo-Gaussian and rank-based optimal tests for random individual effects in large n small T panels

D. Paindaveine, M. Hallin, Nezar Bennala, 2012 .

Rank‐based Optimal Tests for Random Effects in Panel Data

D. Paindaveine, M. Hallin, Nezar Bennala, 2010 .

Multivariate Signed-Rank Tests in Vector Autoregressive Order Identification

Marc Hallin, Davy Paindaveine, D. Paindaveine, 2004 .

Chernoff-Savage and Hodges-Lehmann Results for Wilks' Test of Multivariate Independence

D. Paindaveine, M. Hallin, Marc Hallin, 2008, 0805.2305.

A unified and elementary proof of serial and nonserial, univariate and multivariate: Chernoff-Savage results

D. Paindaveine, 2004 .

Revisiting the name variant of the two-children problem

D. Paindaveine, P. Spindel, 2022, The American Statistician.

On the estimation of cross-information quantities in rank-based inference

D. Paindaveine, M. Hallin, D. Cassart, 2010 .

A General Method for Constructing Pseudo-Gaussian Tests

Marc Hallin, Davy Paindaveine, D. Paindaveine, 2008 .

Nonparametric Optimal Tests for Independence in the Elliptical VAR Model

D. Paindaveine, M. Hallin, M. Bramati, 2005 .

Optimal rank-based tests for homogeneity of scatter

Marc Hallin, Davy Paindaveine, D. Paindaveine, 2008, 0806.2963.

Measuring, Modeling, and Forecasting Volatility and Correlations from High-Frequency Data

D. Paindaveine, Harry-Paul Vander Elst, 2016 .

Discussion of “Multivariate Functional Outlier Detection”, by Mia Hubert, Peter Rousseeuw and Pieter Segaert

Germain Van Bever, D. Paindaveine, 2015, Statistical Methods & Applications.

Computing multiple-output regression quantile regions

D. Paindaveine, M. Siman, 2012, Comput. Stat. Data Anal..

Signed-rank tests for location in the symmetric independent component model

Klaus Nordhausen, Hannu Oja, Davy Paindaveine, 2009, J. Multivar. Anal..

Parametric and nonparametric test for multivariate independence in IC models

Hannu Oja, Sara Taskinen, Davy Paindaveine, 2009 .

Parametric and semiparametric inference for shape: the role of the scale functional

Marc Hallin, Davy Paindaveine, D. Paindaveine, 2006 .

On directional multiple-output quantile regression

Miroslav Siman, Davy Paindaveine, D. Paindaveine, 2011, J. Multivar. Anal..

Conditional quantile estimation based on optimal quantization: From theory to practice

Davy Paindaveine, Jérôme Saracco, Isabelle Charlier, 2015, Comput. Stat. Data Anal..

QuantifQuantile: An R Package for Performing Quantile Regression Through Optimal Quantization

Davy Paindaveine, Jérôme Saracco, Isabelle Charlier, 2015, R J..

A Chernoff-Savage result for shape: on the non-admissibility of pseudo-Gaussian methods

Davy Paindaveine, D. Paindaveine, 2006 .

Computing multiple-output regression quantile regions from projection quantiles

Davy Paindaveine, Miroslav Šiman, D. Paindaveine, 2011, Computational Statistics.