References of "Verdebout, Thomas"
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See detailApplied Directional Statistics : Modern Methods and Case Studies
Ley, Christophe UL; Verdebout, Thomas

Book published by Chapman and Hall/CRC (2019)

This book collects important advances in methodology and data analysis for directional statistics. It is the companion book of the more theoretical treatment presented in Modern Directional Statistics ... [more ▼]

This book collects important advances in methodology and data analysis for directional statistics. It is the companion book of the more theoretical treatment presented in Modern Directional Statistics (CRC Press, 2017). The field of directional statistics has received a lot of attention due to demands from disciplines such as life sciences or machine learning, the availability of massive data sets requiring adapted statistical techniques, and technological advances. This book covers important progress in bioinformatics, biology, astrophysics, oceanography, environmental sciences, earth sciences, machine learning and social sciences. [less ▲]

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See detailModern Directional Statistics
Ley, Christophe UL; Verdebout, Thomas

Book published by Chapman and Hall/CRC (2017)

Modern Directional Statistics collects important advances in methodology and theory for directional statistics over the last two decades. It provides a detailed overview and analysis of recent results ... [more ▼]

Modern Directional Statistics collects important advances in methodology and theory for directional statistics over the last two decades. It provides a detailed overview and analysis of recent results that can help both researchers and practitioners. Knowledge of multivariate statistics eases the reading but is not mandatory. The field of directional statistics has received a lot of attention over the past two decades, due to new demands from domains such as life sciences or machine learning, to the availability of massive data sets requiring adapted statistical techniques, and to technological advances. This book covers important progresses in distribution theory, high-dimensional statistics, kernel density estimation, efficient inference on directional supports, and computational and graphical methods. [less ▲]

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See detailOne-step R-estimation in linear models with stable errors
Hallin, Marc; Swan, Yvik UL; Verdebout, Thomas et al

in Journal of Econometrics (2013), 172(2), 195--204

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See detailOptimal rank-based inference for spherical location
Ley, Christophe; Swan, Yvik UL; Thiam, Baba et al

in Statistica Sinica (2013), 23

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See detailEfficient ANOVA for directional data
Ley, Christophe; Swan, Yvik UL; Verdebout, Thomas

E-print/Working paper (2012)

In this paper we tackle the ANOVA problem for directional data (with particular emphasis on geological data) by having recourse to the Le Cam methodology usually reserved for linear multivariate analysis ... [more ▼]

In this paper we tackle the ANOVA problem for directional data (with particular emphasis on geological data) by having recourse to the Le Cam methodology usually reserved for linear multivariate analysis. We construct locally and asymptotically most stringent parametric tests for ANOVA for directional data within the class of rotationally symmetric distributions. We turn these parametric tests into semi-parametric ones by (i) using a studentization argument (which leads to what we call pseudo-FvML tests) and by (ii) resorting to the invariance principle (which leads to efficient rank-based tests). Within each construction the semi-parametric tests inherit optimality under a given distribution (the FvML distribution in the first case, any rotationally symmetric distribution in the second) from their parametric antecedents and also improve on the latter by being valid under the whole class of rotationally symmetric distributions. Asymptotic relative efficiencies are calculated and the finite-sample behaviour of the proposed tests is investigated by means of a Monte Carlo simulation. We conclude by applying our findings on a real-data example involving geological data. [less ▲]

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