Page Personnelle de Sophie DABO-NIANG





English Version



Adresse :
Université de Lille
Domaine du pont de bois                                                                                                                    CV                                                                             
Laboratoire LEM UMR CNRS 9221, Bureau F 1.05
BP 149, 59653 Villeneuve d’ascq cedex 

Tél :  (33) 320416510
Fax : (33) 320416171
Email : sophie.dabo@univ-lille3.fr


Fonction

  Professeure des universités en mathématiques appliquées

  Responsable de l’axe MéQAME du laboratoire LEM (Lille Economie et Management)


Thèmes de Recherche

Publications récentes


Dabo-Niang, S et Rhomari, N (2009). Kernel regression estimate in a Banach space.Journal of statistical planning and inference. 139, 1421-1434.

Dabo-Niang, S et Guillas S (2010). Functional semi-parametric partially linear model with autoregressive errors. Journal of multivariate analysis, 101, 2, 307-315.

Dabo-Niang, S, Yao, A-F, Pischedda, L, Cuny, P et Gilbert, F. (2010). Spatial mode estimation for functional random fields with application to bioturbation problem.
Stochastic Environmental Research and Risk Assessment (SERRA), 24, 4, 487-497.

Bensaid, N et Dabo-Niang, S. (2010). Frequency polygons for continuous random fields. Stochastic Processes and Statistical Inference, 13,1, 55-80.

\item Dabo-Niang, S et Laksaci, A. (2010). Note on conditional mode estimation for functional dependent data. Statistica, Vol LXX (1), 83-94.

Abdi, S, Abdi, A, Dabo-Niang, S et Diop, A. (2010). Consistency of a nonparametric conditional quantile estimator for random fields.
Mathematical Methods and Statistics, 2010, Vol. 19, No. 1, 1-21.

Dabo-Niang, S et Thiam, B. (2010). $L_1$ consistency of a kernel estimate of spatial conditional quantile. Statistics and probability letters, Vol. 80 (17-18), 1447-1458.

Abdi A, Abdi, S, Dabo-Niang, S et Diop, A. (2010). Estimation non-paramétrique du mode conditionnel spatial. C. R., Math., Acad. Sci. Paris. Vol. 348 (13-14), 815-819.

Dabo-Niang, S, Francq, C et Zakoian, J-M.  (2010).  Combining parametric and nonparametric approaches for time series prediction. JASA, Vol 105 (492), 1554-1565.

Benrabah, O, Dabo-Niang S. et Hamdad, L. (2010). Kernel density estimation for linear processes with dependent innovations. Journal of Statistics: Advances in Theory and Applications, Vol 4, 1, 41-72.

Dabo-Niang, S, Kaid, Z. et Laksaci , A (2011).  Sur la régression quantile pour variable explicative fonctionnelle : Cas des données spatiales. C. R., Math., Acad. Sci. Paris. Vol 349, 23-24, 1287-1291.

Abdi A, Abdi, S, Dabo-Niang, S et Diop, A. (2011). Asymptotic normality of a nonparametric conditional quantile estimator for random fields. Advances in Decision Sciences.
Article ID 462157, doi:10.1155/2011/462157.

Dabo-Niang, S, Rachdi M et Yao, A-F. (2011).  Spatial kernel regression estimation and prediction for functional random fields. Far east journal of Statistics. Volume 37, Issue 2, Pages 77 - 113.

Dabo-Niang, S et Laksaci, A. (2012). Nonparametric quantile regression estimation for functional dependent data. Communication in Statistics: Theory and Methods. 41, 1254-1268.

Chebana, F, Dabo-Niang, S et Ouarda, T. (2012).  Explanatory functional flood frequency analysis. Water Resources Research, 48, W04514, doi:10.1029/2011WR011040.

Dabo-Niang, S, Kaid, Z. et Laksaci, A (2012). On spatial conditional mode estimation for a functional regressor. Statistics and probability letters, 82 (2012) 1413-1421.

Dabo-Niang, S et Zoueu, J. (2012). Using kriging to resolve malaria-infected erythrocyte contents. Journal of Microscopy. DOI: 10.1111/j.1365-2818.2012.03637., 247 (3), 240-251.

Dabo-Niang, S, Kaid, Z. et Laksaci, A (2012).     Spatial conditional quantile regression: weak consistency of a kernel estimate. Revue Roum Math Pures Appl, 4, 311-339.
  
Dabo-Niang, S et Yao, A-F. (2013). Spatial kernel density estimation for functional random variables. Metrika, 76(1):19-52.

Dabo-Niang, S; Abdi, S; Abdi, A, et Diop, A. (2014). Consistency of a nonparametric conditional mode estimator for random fields. Statistical Methods and Application.  DOI : 10.1007/s10260-013-0239-2.

Dabo-Niang, S., Hamdad, L., Ternynck, C., Yao, A.-F.  (2014). A kernel spatial density estimation with applications to spatial clustering and Monsoon Asia Drought Atlas analysis.  SERRA, 28, 2075-2099.

Dabo-Niang, S, Kaid, Z. et Laksaci, A (2015). On spatial conditional quantile estimation for a functional regressor. Advances in Statistical Analysis. DOI 10.1007/s10182-014-0233-5

Dabo-Niang, Ternynck, C., Yao, A.-F.  (2015). A new spatial regression estimator in the multivariate context. \textit{C. R., Math., Acad. Sci. Paris}. To appear.

Bouka, S., Dabo-Niang, S., Nkiet, G-M (2015). Non-parametric level set estimation for spatial data. \textit{Advances and Application in Statistics, 46 (2), 119-158.

Amiri, A, Dabo-Niang et Yahaya, M (2016). Non-parametric recursive density estimation for spatial data. C. R., Math., Acad. Sci. Paris, 354 (2), 205-210, doi :10.1016/j.crma.2015.10.010.

Ternynck, C., Ali Ben Alaya, M., Chebana, F., Dabo-Niang, S., Ouarda, T. B. M. J. (2016) Streamflow hydrograph classification using functional data analysis.
Journal of Hydrometeorology, 17(1), DOI : 10.1175/JHM-D-14-0200.1.

Dabo-Niang, S, Guillas, S et Ternynck, C. (2016). More efficient kernel functional spatial regression estimation with autocorrelated errors.
Journal of Multivariate Analysis, 147, 168-182, doi :10.1016/j.jmva.2016.01.007

Dabo-Niang, Ternynck, C., Yao, A.-F. (2016). Nonparametric prediction in the multiva- riate spatial context. 
Journal of Nonparametric Statistics. 10.1080/10485252.2016.1164313.

Masselot, P., Dabo-Niang, S., Chebana, F. et Ouarda, T B.M.J. (2016). Streamflow forecasting using functional regression. Journal of Hydrology, 538C, 754-766. doi : 10.1016/j.jhydrol.2016.04.048

André, M., Dabo-Niang, S., Soubdhan, T. et Ould-Baba, H. (2016). Predictive spatio- temporal model for spatially sparse global solar radiation data. Energy, 111, 599-608. doi :10.1016/j.energy.2016.06.004

Amiri, A et Dabo-Niang, S. (2017). Density estimation over spatio-temporal data stream. Econometrics and Statistics ; https ://doi.org/10.1016/j.ecosta.2017.08.005.

Ahmed, M.S, Attouch, M. et Dabo-Niang, S. (2017). Functional Binary Choice Models with Choice-Based Sampling. Econometrics and Statistics ; https://doi.org/10.1016/j.ecosta.2017.07.001

Ahmed, M-S., Broze, L., Dabo-Niang, S., Gharbi, Z. (2018). Regression models for spa- tially distributed autoregressive functional data. Dans Wiley book ; Geostatistical Functional Data Analysis :

Theory and Methods. Editors : Jorge Mateu, Ramon Giraldo. A paraître.

Dabo-Niang, S., Ternynck, C., Thiam, B. et Yao, A-F. (2018). Non-parametric statistical analysis of spatially distributed functional data. Dans Wiley book ; Geostatistical Functional Data Analysis :
Theory and Methods. Editors : Jorge Mateu, Ramon Giraldo. A paraître.


Vandewalle, V., Preda, C., Dabo-Niang, S. (2018). Clustering spatial functional data. Dans Wiley book ; Geostatistical Functional Data Analysis : Theory and Methods.
Editors : Jorge Mateu, Ramon Giraldo. A paraître.


Giraldo, R., Dabo-Niang, S., Martinez, S. (2018). Statistical modeling of spatial big data : An approach from a functional data analysis perspective. Statistics and Probability Letters ; https ://doi.org/10.1016/j.spl.2018.02.025


Edition de livre

Dabo-Niang, S et Ferraty, F. (2008). Functional and Operatorial Statistics, Springer-Verlag, New-York.

Articles soumis, en révision ou en cours


  1. Ahmed, M.S, Attouch, M.K, Dabo-Niang, S, Diop. (2018).  k-nearest neighbors method estimation of regression function for spatial dependent data
  2.   Bassene, A, Dabo-Niang, S et Diop, A. (2017). Conditional tail index estimation for random fields : fixed design case
  3. Dabo-Niang, S et Thiam, B. (2017). Nonparametric estimation of a regression function for spatial data with errors.
  4. Bassene, A, Dabo-Niang, S et Diop, A. (2017). Kernel estimation of conditional tail index and quantile estimation for random fields
  5. Chiu, Y., Dabo-Niang, S., Chebana, F. et Ouarda, T B.M.J. (2017). Streamflow forecas- ting using functional time series. A soumettre prochainement.
  6. Curceac, S.,Ternynck, C., Ali Ben Alaya, M., Chebana, F., Dabo-Niang, S., Ouarda, T. B. M. J. (2018). Short-term air temperature forecasting using nonparametric Functional Data Analysis and SARMA models.
  7. Drewsh, E, Dabo-Niang, S, Foncel, J et Torres, O. (2018). Binary Choice Models With Choice-Based Sampling and application to VADS Cancer in Nord Pas De Calais.

Rapports de recherche, Préprints

  1. Dabo-Niang, S.  Two kernel density estimators in an infinite dimensional space: Application to processes of diffusion type. Publications CREST N° 2001-05 (2001).
  2. Dabo-Niang, S.  Density estimation by orthogonal series in an infinite dimensional space: Application to processes of diffusion type. Publications ISUP-LSTA, 2002-4 (2002).
  3. Dabo-Niang, S et Rhomari, N. Nonparametric regression estimation when the regressor takes its values in metric space. Publications ISUP-LSTA, 2002-9 (2002).
  4. Dabo-Niang, S et Maumy, M (2003).  Loi du logarithme itéré pour l'estimateur de la densité dans le cas multivarié. Préprint
  5. Dabo-Niang, S et Emilion, R (2003). Résultats de différentiation de mesures dans un espace de Banach : Application à l'estimation fonctionnelle.  Préprint.

Enseignements : 2013-2018


Manifestations scientifiques