Articles dans des revues avec comité de lecture (81)
11.
Paindaveine, D., Rasoafaraniaina, R. J., & Verdebout, T. (2021). Preliminary test estimation in ULAN models. Scandinavian journal of statistics, 48, 689-707.
12.
Paindaveine, D., Remy, J., & Verdebout, T. (2020). Testing for principal component directions under weak identifiability. Annals of statistics, 48(1), 324-345. doi:10.1214/18-AOS1805
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Cutting, C., Paindaveine, D., & Verdebout, T. (2020). On the power of axial tests of uniformity on spheres. Electronic Journal of Statistics, 14(1), 2123-2154. doi:10.1214/20-EJS1716
14.
Paindaveine, D., Remy, J., & Verdebout, T. (2020). Sign Tests for Weak Principal Directions. Bernoulli, 29, 2987-3016.
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Charlier, I., Paindaveine, D., & Saracco, J. (2020). Multiple-output quantile regression through optimal quantization. Scandinavian journal of statistics, 47, 250-278. doi:10.1111/sjos.12426
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García-Portugués, E., Paindaveine, D., & Verdebout, T. (2020). On Optimal Tests for Rotational Symmetry Against New Classes of Hyperspherical Distributions. Journal of the American Statistical Association, 115, 1873–1887. doi:10.1080/01621459.2019.1665527
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Paindaveine, D., & Verdebout, T. (2020). Inference for spherical location under high concentration. Annals of statistics, 48, 2982-2998.
18.
Paindaveine, D., & Verdebout, T. (2020). Detecting the Direction of a Signal on High-dimensional Spheres: Non-null and Le Cam Optimality Results. Probability theory and related fields, 176, 1165-1216.
19.
Paindaveine, D., & Van Bever, G. (2019). Tyler shape depth. Biometrika, 106(4), 913-927. doi:10.1093/biomet/asz039
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Pandolfo, G., Paindaveine, D., & Porzio, G. (2018). Distance-based depths for directional data. Canadian journal of statistics, 46(4), 593-609. doi:10.1002/cjs.11479
21.
Paindaveine, D., & Van Bever, G. (2018). Halfspace depths for scatter, concentration and shape matrices. Annals of statistics, 46(6B), 3276-3307. doi:10.1214/17-AOS1658
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Paindaveine, D., & Verdebout, T. (2017). Inference on the mode of weak directional signals: A Le Cam perspective on hypothesis testing near singularities. Annals of statistics, 45, 800-832.