Publications

1. Articles publiés dans des revues internationales à comité de lecture 

• Mokkadem, A. Pelletier, M. and Thiam, B. (2006). Large and moderate deviations principles for the recursive kernel estimators of the multivariate density and its partial derivatives. Serdica Math. J., vol. 32 (4), 323–354.

• Mokkadem, A. Pelletier, M. and Thiam, B. (2008). Large and moderate deviations principles for kernel estimators of the multivariate regression. Mathematical Methods of Statistics, vol. 17 (2), 1–27.

• Dabo-Niang, S. and Thiam, B. (2010). Robust quantile estimation and prediction for spatial processes. Statistics and Probability Letters, vol. 80, (17-18), 1447–1458.

• Picard, F., Lebarbier, E., Hoebeke, M., Rigaill, G., Robin, S. and Thiam, B. (2011). Joint segmentation, calling and normalization of multiple CGH profiles. Biostatistics, vol. 12, Number 3, Pages 413–428.

• Mokkadem A., Pelletier, M. and Thiam, B. (2011). Joint behaviour of semirecursive kernel estimators of the location and of the size of the mode of a probability density function. Journal of Probability and Statistics, doi :10.1155/2011/564297.

• Ley, C., Swan, Y., Thiam, B. and Verdebout, T. (2013). Optimal R-estimator for spherical location. Statistica Sinica, vol. 23, (1), 305–333.

• Amiri, A., Crambes, C. and Thiam, B. (2014). Recursive estimation of nonparametric regression with functional covariate. Computational Statistics and Data Analysis, vol. 69, 154–172.

• Amiri, A. and Thiam, B. (2014). Consistency of the recursive nonparametric regression estimation for dependent functional data. Journal of Nonparametric Statistics, vol. 26 (3), 471–487.

• Amiri, A. and Thiam, B. (2014). A smoothing stochastic algorithm for quantile estimation. Statistics and Probability Letters, vol. 93, 116–125.

• Khardani, S. and Thiam, B. (2016). Strong consistency result of a nonparametric conditional mode estimator under random censorship for functional regressors. Communications in Statistics, Theory and Methods, vol. 45 (7), 1863–1875.

• Amiri, A. Thiam, B. and Verdebout, T. (2017). On the estimation of the density of a directional data stream. Scandinavian Journal of Statistics, vol. 44 (1), 249–267.

• Amiri, A. and Thiam, B. (2018). Regression estimation by local polynomial fitting for multivariate data stream. Statistical Papers, vol. 59, (2), 813–843.

• Thiam, B. (2019). Relative error prediction in nonparametric deconvolution regression model. Statistica Nerlandica, vol. 73, (1), 63–77.

• Dabo-Niang, S., Ternynck, C., Thiam, B. et Yao, A-F. (2020). Nonparametric statistical analysis of spatially distributed functional data. A paraître dans Wiley book ; Geostatistical Functional Data Analysis : Theory and Methods. Editors : Jorge Mateu, Ramon Giraldo. John Wiley and Sons, Chichester, UK. ISBN : 978-1-119-38784-8.

• Dabo-Niang, S. and Thiam, B.(2020). Kernel regression estimation with errors-in-variables for random fields. Afrika Mathematica, vol 31, 29–56.

• Dabo-Niang, S., Thiam, B. and Verdebout, T. (2022). Asymptotic efficiency of some nonparametric tests for location on hyperspheres, Statistics and Probability Letters, vol. 188, art. 109524.

• Amiri, A. and Thiam, B. (2025). Nonparametric regression for locally stationary functional data. A paraître dans Communications in Statistics, Theory and Methods.

2. Prépublications

• Bassene, A, Dabo-Niang, S, Diop., A. Thiam, B. Conditional tail index estimation for random fields : fixed design case.

• Bassene, A, Dabo-Niang, S, Diop., A. Thiam, B. Kernel estimation of conditional tail index and quantile estimation for random fields.