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Accessibilité

Baba Thiam

Maître de conférences CNU : SECTION 26 - MATHEMATIQUES APPLIQUEES ET APPLICATIONS DES MATHEMATIQUES Laboratoire / équipe

Publications

hal-01812238

Sophie Dabo-Niang, Camille Ternynck, Baba Thiam, Anne-Françoise Yao

Non-parametric statistical analysis of spatially distributed functional data

Ramon Giraldo; Jorge Mateu. Geostatistical Functional Data Analysis, Wiley, 2021, 978-1-119-38784-8. ⟨10.1002/9781119387916.ch8⟩

hal-02334993

Sophie Dabo-Niang, Baba Thiam

Kernel regression estimation with errors-in-variables for random fields

Afrika Matematika, 2020, 31, pp.29-56. ⟨10.1007/s13370-019-00654-7⟩

hal-01824274

Baba Thiam

Relative error prediction in nonparametric deconvolution regression model

Statistica Neerlandica, 2018, ⟨10.1111/stan.12135⟩

hal-01592782

Aboubacar Amiri, Baba Thiam, Thomas Verdebout

On the Estimation of the Density of a Directional Data Stream

Scandinavian Journal of Statistics, 2016, 44 (1), pp.249--267. ⟨10.1111/sjos.12252⟩

hal-01592783

Aboubacar Amiri, Baba Thiam

Regression estimation by local polynomial fitting for multivariate data streams

Statistical Papers, 2016, 59, pp.813-843. ⟨10.1007/s00362-016-0791-6⟩

hal-01526023

Khardani Salah, Baba Thiam

Strong consistency result of a non parametric conditional mode estimator under random censorship for functional regressors

Communications in Statistics - Theory and Methods, 2016, 45 (7), pp.1863--1875. ⟨10.1080/03610926.2013.867997⟩

hal-01206832

Sophie Dabo-Niang, Baba Thiam

Nonparametric estimation of a regression function for spatial data with errors.

2015

hal-01818838

Aboubacar Amiri, Christophe Crambes, Baba Thiam

Recursive estimation of nonparametric regression with functional covariate

Computational Statistics and Data Analysis, 2014, 69, pp.154 - 172. ⟨10.1016/j.csda.2013.07.030⟩

hal-00815205

Aboubacar Amiri, Baba Thiam

Consistency of the recursive nonparametric regression estimation for dependent functional data.

2013

hal-00750894

Aboubacar Amiri, Christophe Crambes, Baba Thiam

Recursive estimation of nonparametric regression with functional covariate.

2012

hal-00201748

Abdelkader Mokkadem, Mariane Pelletier, Baba Thiam

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, 2011, pp.ID 564297. ⟨10.1155/2011/564297⟩

hal-01019859

Franck Picard, Mark Hoebeke, Guillem Rigaill, Baba Thiam, Stephane Robin

Joint segmentation, calling, and normalization of multiple CGH profiles

Biostatistics, 2011, 12 (3), pp.413-428. ⟨10.1093/biostatistics/kxq076⟩

hal-00450101

Sophie Dabo Niang, Baba Thiam

Robust quantile estimation and prediction for spatial processes

2010

hal-00958115

Sophie Dabo-Niang, Baba Thiam

Robust quantile estimation and prediction for spatial processes

Statistics and Probability Letters, 2010, 80 (17-18), pp.1447-1458. ⟨10.1016/j.spl.2010.05.012⟩

hal-00678977

Abdelkader Mokkadem, Mariane Pelletier, Baba Thiam

Large and moderate deviations principles for kernel estimators of the multivariate regression.

Mathematical Methods of Statistics, 2008, 17 (2), pp.146-172. ⟨10.3103/S1066530708020051⟩

hal-00136115

Abdelkader Mokkadem, Mariane Pelletier, Baba Thiam

Large and moderate deviations principles for kernel estimators of the multivariate regression

2007

tel-00131199

Baba Thiam

Estimation récursive de fonctionnelles

Mathématiques [math]. Université de Versailles-Saint Quentin en Yvelines, 2006. Français. ⟨NNT : ⟩

hal-00017207

Abdelkader Mokkadem, Mariane Pelletier, Baba Thiam

Large and moderate deviations principles for recursive kernel estimators of a multivariate density and its partial derivatives.

2006

Recherche

Type de document

Année

  • 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 Statis- tics, 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 condi- tional 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. (2018). 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.
  • Dabo-Niang,S.andThiam,B.(2020).Kernel regression estimation with errors-in-variables for random fields, Afrika Mathematica, vol 31, 29–56.