Publications

  1. Mohammd Amine Meraou, Fatimah Alshahrani, Ibrahim M. Almanjahie and Mohammed Kadi Attouch,. (2023). The Exponential T-X Gompertz Model for Modeling Real Lifetime Data: Properties and Estimation, Chiang Mai Journal of Sciences, 50(5), https://doi.org/10.12982/CMJS.2023.048.
  2. Md. Mahabubur Rahman,  Ahmed M. Gemeay, Md. Awwal Islam Khan,  Mohammed Amine Meraou,  M. E. Bakr, Abdisalam Hassan Muse, Eslam Hussam, and Oluwafemi Samson Balogun. (2023). A new modified cubic transmuted-G family of distributions: Properties and different methods of estimation with applications to real-life data, AIP Advances, 13, 095025, https://doi.org/10.1063/5.0170178.
  3. Shama, M.S., Alharthi, A.S., Almulhim, F.A, Gemeay, A.M, Meraou, M.A, Manahil, S.M, Eslam, H, Aljohani, M. (2023). Modified generalized Weibull distribution: theory and applications. Sci Rep 13, 12828, https://doi.org/10.1038/s41598-023-38942-9.
  4. Aijaz Ahmad, Muzamil Jallal, Mutua Kilai ,M. Yusuf , M. A. Meraou. (2023). The Novel Kumaraswamy Power Frechet Distribution with Data Analysis Related To Diverse Scientific Areas. Alexandaria Journal.
  5. AIjaz Ahmad, S. Qurat ul Ain,Mintodé Nicodème Atchade , M. A. Meraou. (2023). New Hyperbolic Sine-Generator With an Example of Rayleigh Distribution: Simulation and Data Analysis in Industry. Alexandaria Journal.
  6. I. Almanjahie, O. Fetitah, M. Attouch and T. Benchikh. (2023). Functional nonparametric predictions in food industry using near-infrared spectroscopy measurement, Computers, Materials and Continua 74(3):6307-6319.
  7. S. Guenani, W. Bouabsa, M. Attouch, O. Fetitah (2023) kNN robustification equivariant nonparametric regression estimators for functional ergodic data, Hacettepe Journal of Mathematics and Statistics, 2023, 1-17.
  8. O Litimein, A Laksaci, B Mechab, S Bouzebda,  Local linear estimate of the functional expectile regression. Statistics & Probability Letters 192, 109682.
  9. Omar Fetitah,  Mohammed Kadi Attouch, Salah Khardani,  Ali Righi.  (2023). Robust nonparametric equivariant regression for functional data with responses missing at random. Metrika, https://doi.org/10.1007/s00184-023-00898-1.
  10. O. Litimein, F. Alshahrani, S. Bouzebda, A. Laksaci and Boubaker Mechab, Kolmogorov Entropy for Convergence Rate in Incomplete Functional Time Series: Application to Percentile and Cumulative Estimation in High Dimensional Data, Entropy 2023, 25(7), 1108. https://www.mdpi.com/1099-4300/25/7/1108.
  11. Omar Omari, Torkia Merouan, Boubaker Mechab, Uniform Convergence Of Nonparametric Conditional Hazard Function In The Single Functional Index Modeling For Dependent Data , Journal Of Science And Arts Volume 23, Issue 1, 91-106, 2023 https://josa.ro//docs/josa_2023_1/cuprins.htm.
  12.   F. Alshahrani, I.M. Almanjahie, T. Benchikh, O. Fetitah and Mohammed Kadi Attouch, “Asymptotic Normality of onparametric Kernel Regression Estimation for Missing at Random Functional Spatial Data”, Journal of Mathematics, Volume 2023, Hindawi,  Article ID 8874880, 20 pages, https://doi.org/10.1155/2023/8874880.
  13. Mustapha  Mohammedi, Salim Bouzebda, Ali Laksaci et Oussama Bouanani , Asymptotic normality of the k-NN single index regression estimator for functional weak dependence data, Communication in Statistics- Theory and Methods  (2023). https://www.tandfonline.com/eprint/SK3HTEKZNFJEFZY9CWAJ/full?target=10.1080/03610926.2022.2150823. https://doi.org/10.1080/03610926.20
  14.  MALIKA HAMMAD, ZOUAOUIA BOULENOIR, SAMIR BENAISSA ;  EXPONENTIAL TYPE INEQUALITIES AND ALMOST COMPLETE CONVERGENCE OF THE OPERATOR ESTIMATOR OF FIRST-ORDER AUTOREGRESSIVE IN HILBERT SPACE GENERATED BY WOD ERROR.  Journal of Science and Arts Volume 23, Issue 3, pp. 671-680, 2023.
  1. M. Alamer, O. Fetitah, I. Almanjahie and M. Attouch. (2022). Modern Functional Statistical Analysis: Application to Air Pollutant in London Marylebone Road, Chiang Mai Journal of Science, 49(2) : 511-523.
  2.  M. Attouch, O. Fetitah and H. Louhab. (2022). Asymptotic normality of the robust equivariant estimator for functional nonparametric models, Mathematical Problems in Engineering, 2022: 1-15.
  3.  N. Bellatrach, W. Bouabsa, M. Attouch, O. Fetitah. (2022). M-Regression Estimation with the k Nearest Neighbor’s Smoothing Under Quasi-associated Data in Functional Statistics, Applications and Applied Mathematics: An InternationalJournal (AAM), 7(2): 333 – 365.
  4.  SA Benchiha, AI Al-Omari, G Alomani, (2022), Goodness-of-Fit Tests for Weighted Generalized Quasi-Lindley Distribution Using SRS and RSS with Applications to Real Data, Axioms 11 (10), 490.
  5. AI Al-Omari, SA Benchiha, IM Almanjahie, (2022), Efficient estimation of two-parameter Xgamma distribution parameters using ranked set sampling design, Mathematics 10 (17), 3170
  6. Mohammed A. Meraou, Noriah M. Al-Kandari, Mohammad Z. Raqab & Debasis Kundu. (2022). Analysis of skewed data by using compound Poisson exponential distributionwith applications to insurance claims, Journal of Statistical Computation and Simulation, DOI:10.1080/00949655.2021.1981324.
  7. Mohammed A. Meraou, Noriah M. Al-Kandari, Mohammad Z. Raqab & DebasisKundu. (2022). Univariate andBivariate Models Based on Random Sum of Variates with Related Application, Journal of Statistical Theory and Practice.
  8. Ehab M. Almetwally1, Mohammed Amine Meraou. (2022). Application of Environmental Data with New Extension of Nadarajah-Haghighi Distribution, Computational Journal of Mathematical and Statistical Sciences, 1(1), 26–41.  DOI:10.21608/cjmss.2022.271186.
  9. A Goutal, B Mechab, O Fetitah, T Merouan, (2022). Asymptotic Normality of the Conditional Hazard Function In the Local Linear Estimation Under Functional Mixing Data. Applications & Applied Mathematics 17 (2).
  10. Chouaf Abdelhak, Abdelmalek Gagui (2022).  On the nonparametric estimation of the conditional hazard estimator in a single functional index.  Statistics in Transition New Series 23(2):89–105.    DOI: 10.2478/stattrans-2022-0018.
  11. Allal Saadaoui, Fadila Benaissa , Chouaf Abdelhak (2022). On the local linear estimation of a generalized regression function with spatial functional data.  Communication in Statistics- Theory and Methods. DOI:  10.1080/03610926.2022.2064499
  12. Ataouia Bakhtaoui and Faiza Limam-Belarbi, Local Linear Estimation of the Trimmed Regression for Censored Functional Data, 36:14 (2022), 4919–4933 https://doi.org/10.2298/FIL2214919B
  13. Assia Bourouba , Nesrine Hamidi , Boubaker Mechab, Ouahiba Litimein, Strong Consistency Rate Of The Conditional Quantile Estimator With Data Missing At Random Journal Of Science And Arts Volume 22, Issue 4, Pp. 811-820, 2022https://josa.ro//docs/josa_2022_4/cuprins.htm
  14. Goutal, Amina; Mechab, Boubaker; Fetitah, Omar; and Merouan Torkia, Asymptotic Normality of the Conditional Hazard Function in the Local Linear Estimation Under Functional Mixing Data, Applications and Applied Mathematics: An International Journal (AAM), Vol. 17, Iss. 2; 308-332, 2022 https://digitalcommons.pvamu.edu/aam/vol17/iss2/
  15. Zoubeyr Kaddour, Abderrahmane Belguerna, Samir Benaissa, New Tail Probability Type Concentration Inequalities and Complete Convergence  for WOD Random Variables, Turkish Journal of Computer and Mathematics Education Vol.13 No.02 (2022), 151-156. https://turcomat.org/index.php/turkbilmat/article/view/12159
  16. Zoubeyr Kaddour, Abderrahmane Belguerna, Samir Benaissa, New Tail Probability Type Inequalities And Complete Convergence For Wod Random Variables With Application To Linear Model Generated By Wod Errors, Journal of Science and Arts Volume 22, Issue 2, pp. 309-318, 2022 https://www.josa.ro//index.html?https%3A//www.josa.ro//josa.html
  17. Zoubeyr Kaddour, Abderrahmane Belguerna, Samir Benaissa, Probability tail for linearly negative quadrant dependent random variables of partial sums and application to linear model, J. Innov. Math. Comput. Sci. 2(2) (2022), 14–22http://jiamcs.centre-univ-mila.dz/index.php/jiamcs/article/view/v2i2_26.
  18.  Salim Bouzebda, Ali Laksaci et Mustapha Mohammedi The k-Nearest Neighbors method in single index regression model for functional quasi-associated times series data, Revista Mathemática Complutense, 31 pp. (2022).  https://doi.org/10.1007/s13163-022-00436-z.
  19.  Salim Bouzebda, Ali Laksaci et Mustapha Mohammedi,  Single index regression model for functional quasi-associated times series data, 29 pp. REVSTAT- Statistical Journal. https://www.ine.pt/revstat/pdf/Singleindexregressionmodel.pdf. https://doi.org/10.57805/revstat.v20i5.391
Contenu d’accordéon
  1. M Benallou, MK Attouch, T Benchikh, O Fetitah. (2021). Asymptotic results of semi-functional partial linear regression estimate under functional spatial dependency. Communications in Statistics-Theory and Methods, 1-21, (2021).
  2. Imane Metmous, Mohammed Kadi Attouch, Boubaker Mechab, Torkia Merouan,  Nonparametric estimation of the conditional distribution function for surrogate data by the regression model,  Applications and Applied Mathematics: An International Journal (AAM).  16(1), 55-74, 2021.https://www.tandfonline.com/doi/full/10.1080/03610926.2019.1580735
  3. AMINA zeblah, Samir benaissa, New tail probability inequalities for widely orthant dependent variables sequence, application to hazard estimator Journal of Applied Mathematics and Statistics: (JAMS).  16(1), 55-74, 2021.
  4. Samir Benaissa, AbdelKader Bahram, Boubaker Mechab. New exponential  probability inequality and complete convergence for random variables sequence with application to model generated by  (JSA) N02(55).pp.437-448.2021.
  5. Fadila Benaissa, Abdelmalek Gagui and Chouaf Abdelhak, Asymptotic properties of a nonparametric conditional density estimator in the local linear estimation for functional data via a functional single index model. Statistical Theory and related Fields. 2021, DOI: 10.1080/24754269.2021.1965948.

  6. Mustapha Mohammedi , Salim Bouzebda,  Ali Laksaci (2021). The consistency and asymptotic normality of the kernel type expectile regression estimator for functional data.  Journal of Multivariate Analysis, 181,104673.

  7. AI Al-Omari, SA Benchiha, IM Almanjahie, (2021), Efficient Estimation of the Generalized Quasi-Lindley Distribution Parameters under Ranked Set Sampling and Applications Mathematical Problems in Engineering.
  8. SA Benchiha, AI Al-Omari, (2021), Generalized quasi Lindley distribution: theoretical properties, estimation methods and applications. Electronic Journal of Applied Statistical Analysis 14 (1)
  9. SA Benchiha, AI Al-Omari, N Alotaibi, M Shrahili, (2021), Weighted generalized Quasi Lindley distribution: Different methods of estimation, applications for Covid-19 and engineering data, AIMS Math 6, 11850-11878
  10. SA Benchiha, AI Al-Omari, (2021), Goodness of Fit Tests for Generalized Quasi Lindley Distribution, Journal of Xi’an Shiyou University, Natural Science Edition, 17(12), 480-495.
  11. Mohammed Amine Meraou1, Mohammad Z. Raqab. (2021).Statistical Properties and Different Estimation Procedures of Poisson–Lindley Distribution, Journal of Statistical Theory and Applications, 20(1), 33-45. DOI: https://doi.org/10.2991/jsta.d.210105.001

  12.  R.J. Abdelghani , M.A. Meraou , M.Z. Raqab. (2021). BIVARIATE COMPOUND DISTRIBUTION BASED ON POISSON MAXIMA OF GAMMA VARIATES AND RELATED APPLICATIONS, International Journal of Applied Mathematics, 34(5), 957-978. doi: http://dx.doi.org/10.12732/ijam.v34i5.6.

  13. Chaima Hebchi, Chouaf Abdelhak (2021). Local linear estimation of conditional cumulative distribution function in the functional data: Uniform consistency with convergence rates. Kybernetika –Praha. DOI: 10.14736/kyb-2021-5-0819

  14. O. Fetitah, I. Almanjahie, MK. Attouch, S. Khardani. (2021). Industrial Food Quality Analysis Using New k-Nearest-Neighbour methods. Computers Materials & Continua. 67(2):2681-2694. DOI: 10.32604/cmc.2021.015469
  15. Mustapha  Mohammedi, Salim Bouzebda et Ali Laksaci. Journal of Multivariate Analysis  (JMVA) , The consistency and asymptotic normality of the kernel type expectile regression estimator for functional data, Volume 181, January 2021, 104673,   https://doi.org/10.1016/j.jmva.2020.104673
  1. Hamza Daoudi, Boubaker Mechab, Zouaoui Chikr Elmezouar, Asymptotic Normality of a Conditional Hazard Function Estimate in the Single Index for Quasi-Associated Data, Communication in Statistics Theory and Methods. 49(3), 513-530, 2020. ISSN : 0361-0926 https://www.tandfonline.com/doi/full/10.1080/03610926.2018.1549248
  2.  Abeidallah, B. Mechab, T. Merouan, Local Linear Estimate of the Point at High Risk: Spatial Functional Data Case, Communication in Statistics Theory and Methods. 49(11), 2561-2584, 2020. 0361-0926. https://www.tandfonline.com/doi/full/10.1080/03610926.2019.1580735
  3. IM Almanjahie, MK Attouch, Z Kaid, H Louhab, Robust equivariant non parametric regression estimators for functional ergodic data, Communications in Statistics-Theory and Methods, 1-17, 2020

  4. Omar Fetitah, Ibrahim M. Almanjahie, Mohammed Kadi Attouch, Ali Righi;  (2020). STRONG CONVERGENCE OF THE FUNCTIONAL NONPARAMETRIC RELATIVE ERROR REGRESSION  ESTIMATOR UNDER RIGHT CENSORING. Math. Slovaca 70, No. 6, 1-22.

  5. Mebsout, M., M. Attouch, and O. Fetitah. « Nonparametric M-regression with scale parameter for functional dependent data. » Applications and Applied Mathematics: An International Journal (AAM) 15.2 (2020): 846-874.
  6. O. Fetitah, I. Almanjahie, MK. Attouch, H. Louhab. (2020). Robust kernel regression estimator of the scale parameter for functional ergodic data with applications. Chilean Journal of Statistics (ChJS). Vol. 11 Issue 2, p73-93.
  7. Mustapha  Mohammedi, Salim Bouzebda et Ali Laksaci,  On the nonparametric estimation of the functional expectile regression, Comptes Rendus – Mathématique,  no. 3. pp. 267—272, https://doi.org/10.5802/crmath.27.

 

  1. A Bachir, IM Almanjahie, MK Attouch , The k Nearest Neighbors Estimator of the M-Regression in Functional Statistics, CMC-COMPUTERS MATERIALS & CONTINUA 65 (3), 2049-2064, 2019.
  2. Habibech M.; Benchikh Tawfik, A comparison study between artificial neural network (ANN) and Genetic algorithms (GA) and Box-Jenkins (BJ) modeling in chaotic time series prediction. International Journal of Tomography and Simulation. Volume 32, Issue Number 4, 2019.
  3. Mohammed Kadi Attouch, Zoulikha Kaid, Hayat Louhab , Volum Asymptotic normality of a robust kernel estimator of the regression function for functional ergodic data: Case of an unknown scale parameter, Comptes Rendus Mathematique 357 (5), 478-481; 2019.
  4. M Attouch, A Laksaci, F Rafaa; On the local linear estimate for functional regression: Uniform in bandwidth consistency;

    Communications in Statistics-Theory and Methods 48 (8), 1836-1853; 2019.

  5. Z Kaid, M Attouch, Z Mastefaoui, A Laksaci, PREDICTION OF MAXIMUM OZONE CONCENTRATION USING BIG DATA MODELS, APPLIED ECOLOGY AND ENVIRONMENTAL RESEARCH 17 (6), 14231-14239, 2019.
  6. Ikhlasse Chebbab , Samir Benaissa, Complete convergence and Maximal inequalities for product sums of WOD sequences, International Journal of Statistics & Economics,2019, 20, 1,1-8. http://www.ceser.in/ceserp/index.php/bse/article/view/5935
  7. Ikhlasse Chebbab , Samir Benaissa, The Complete Convergence for the Parameter Estimator of the First-Order Autoregressive Process Created by WOD Errors , International Journal of Statistics & Economics,2019,20,  1,80-87.
  8. Meriem ELHADDAD, Faiza Belarbi, On the Analysis of Unreliable Markovian Multiserver Queue with Retrials and Impatience, Mathematical Sciences and Applications E-Notes 7(2):205-217, 2019.
    1. Souheyla Chemikh, Faiza Belarbi; Local linear estimation of the nonparametric trimmed regression in functional data, International Journal of Statistics & Economics,  Volume 20, Issue Number: 2, 2019
    http://www.ceser.in/ceserp/index.php/bse/article/view/6035.
  10. Gagui Abdelmalek, CHOUAF Abdelhak, Strong uniform consistency rates of conditional hazard estimator via a functional single-index model . International Journal of Statistics and Economics; IJSE,  2019, Volume 20, Issue Number: 4. http://www.ceser.in/ceserp/index.php/bse

     

  1. T. Benchikh, K. Mankour, Canonical development of second order Banach-valued random element, International Journal of Statistics and Economics, Volume 9, issue 1, 2018.
  2. MS Ahmed, MK Attouch, S Dabo-Niang, Binary functional linear models under choice-based sampling, Econometrics and statistics,  7, 134-152; 2018
    1. L Gasmi, ZC Elmezouar, MK Attouch; Wind power forecasting using neural network and ARIMA models (field of » Kabertene », in southern Algeria),

    INTERNATIONAL JOURNAL OF ECOLOGICAL ECONOMICS & STATISTICS 39 (2), 71-79, 2018.

  4. Goutel, B. Mechab, M.A Issa, Y Souddi, Asymptotic normality of a recursive estimator of a conditional hazard, ProbStat Forum, 36–52, 11,  2018. http://probstat.org.in/PSF-2018-04.pdf
  5. Nesrine Hamidi, Boubaker Mechab, Estimation of the Conditional Quantile for Functional Stationary Ergodic Data with Responses Missing at Random, Journal of Probability and Statistical Science, 16(2), 131-149, 2018. http://www.i-tel.com.tw/jpss/
  6. Hadjer Kebir, Boubaker Mechab, Recursive kernel estimate of the conditional hazard function for functional ergodic data, International Journal of Statistics & Economics, 19(4), 1-13, 2018. http://www.ceser.in/ceserp/index.php/bse/article/view/5680
  7. Torkia Merouan, Boubaker Mechab, Ibrahim Massim, Quadratic error of the conditional hazard function in the local linear estimation for functional data, Afrika Statistika, 13(3), 1759-1777, 2018. https://www.ajol.info/index.php/afst/article/view/181575
    1. Belaïd Mechab, Nadji Chioukh, Boubaker Mechab, Boualem Serier, Probabilistic fracture mechanics for analysis of longitudinal cracks in pipes under internal pressure, Journal of Failure Analysis and Prevention, 18(06), 1643-1651, 2018.                https://link.springer.com/article/10.1007/s11668-018-0564-8.
  9. Faiza Belarbi, Souheyla Chemikh, Ali Laksaci, Local linear estimate of the nonparametric robust regression in functional data, Statistics & Probability Letters, Volume 134, (March 2018), Pages 128-133.
  1. M. Attouch, A. Laksaci and N. Messabihi Nonparametric relative error regression for spatial random variables. Statistical Papers, Volume: 58 Issue: 4 Pages: 987-1008, (2017).
  2. M. Attouch, A. Laksaci and F, Rafaa Local linear estimate of the regression operator by the kNN method. COMPTES RENDUS MATHEMATIQUE, 355 Issue 7; 824-829, (2017).
  3. L. Z. Kara , A. Laksaci, M. Rachdi and Ph. Vieu, Data-driven NN estimation in nonparametric functional data analysis J. Multivariate Anal. 153, 176-188, (2017)
    J. Demongeot, A.
  4. Laksaci, A. Naceri and M. Rachdi Local linear regression modelization when all variables are curves Statistics & Probability Letters, 121, 37-44, (2017).
  5. L. Z. Kara , A. Laksaci, M. Rachdi and Ph. Vieu Uniform in bandwidth consistency results for various kernel estimators involving functional data, J . Nonparametr. Stat. 29, Issue: 1, 85-107, (2017).
  1. F. Benziadi A. Laksaci, and F. Tebboune Recursive kernel estimate of the conditional quantile for functional ergodic data, Comm. Statist. Theory and Methods, 45, 3097–3113,(2016).
  2. W.Mechab and A. Laksaci, Nonparametric relative regression for associated random variables.Metron 74, 75–97 (2016).
  3. F. Benziadi, A. Laksaci and F. Tebboune, Note on conditional quantiles for functional ergodic data. C. R. Math. Acad. Sci. Paris 354, 628–633, (2016).
  4. J. Demongeot, A. Hamie, A. Laksaci, M. Rachdi. Relative-error prediction in nonparametric functional statistics: theory and practice. J. Multivariate Anal. 146 261–268, (2016).
  5. F. Benziadi, A. Gheriballah and A. Laksaci, Asymptotic normality of kernel estimator of $\psi$-regression function for functional ergodic data , New Trends in Mathematical Sciences Volume: 4, 268-282, 633 (2016).
  6. F.Z. Ardjoun L. Ait Hennani, A. Laksaci , A recursive kernel estimate of the functional modal regression under ergodic dependence condition. J. Stat. Theory Pract. 10 (2016), no. 3, 475—496.
  7. J. Demongeot, A. Hamie, A. Laksaci, M. Rachdi. Relative-error prediction in nonparametric functional statistics: Theory and practice .J. Multivariate Anal. 146, 261–268, (2016).
  8. J. Demongeot, A. Laksaci, A. Naceri and M. Rachdi Estimation locale linéaire de la fonction de régression pour des variables hilbertiennes C. R. Math. Acad. Sci. Paris 354, 847-850, (2016)
  1. S. Dabo-Niang, Z. Kaid and A. Laksaci Asymptotic properties of the kernel estimate of the spatial conditional mode when the regressor is functional, AStA Advances in Statistical Analysis, 99, 131–160, (2015).
  2. AZZOUZI, A.s RABHI, S.BENAISSA ,Complete Convergence of Moving Average Processes With Psi-Mixing Sequences,International Journal of Statistics & Economics,2015, Volume 16, Issue Number: 2,1-6.
  3. S. Derrar, A. Laksaci and E. Ould Saïd, On the nonparametric estimation of the functional $\psi$-regression for a random left-truncation model. J. Stat. Theory Pract. 9, 823–849. (2015).
  4. A. Naceri, A. Laksaci and M. Rachdi Exact Quadratic Error of the Local Linear Regression Operator Estimator for Functional Covariates, Functional Statistics and Applications, Selected Papers from MICPS-2013, 79-90, Springer , 2015.
  5. S. Attaoui, A. Laksaci and E. Ould-Said Elias Asymptotic Results for an M-Estimator of the Regression Function for Quasi-Associated Processes, Functional Statistics and Applications, Selected Papers from MICPS-2013, 3-28, Springer, 2015.
  6. T. Benchikh, Approximation of Strictly Stationary Banach-Valued Random Sequence by Fourier Integral, Functional Statistics and Applications, Selected Papers from MICPS-2013,51-58, Springer, 2015.
  1. Rachdi, M., Laksaci, A., Demongeot, J., Abdali, A. and Madani, Theoretical and practical aspects on the quadratic error in the local linear estimation of the conditional density for functional data. Computational Statistics and Data Analysis, 73, 53-68, (2014).
  2. A. Laksaci and B. Mechab Conditional hazard estimate for functional random fields, J. Stat. Theory Pract, 8, 192—220, (2014).
  3. J. Demongeot, A. Laksaci, M. Rachdi and S. Rahmaani On the local linear modelization of the conditional distribution for functional data, Sankhya A 76 328—355, (2014).
  4. S. Semmar and S. Khardani Nonparametric conditional density estimation using recursive kernel with censored data, Electronic Journal of Statistics, 8, 2541-2556. (2014)
  5. A. Bouadjemi Asymptotic normality of the recursive kernel estimate of conditional cumulative distribution function, Journal of Probability and Statistical Science, 12, 117-126, (2014).
  6. Attouch M.K, Belabed Z. The k nearest neighbors estimation of the conditional hazard function for functional data.REVSTAT, 12,273-297, ( 2014)
  7. Benchikh Tawfik. Spectral representation of a Banach-valued stationary random function on a locally compact abelian group. Georgian Mathematical Journal. 21, Issue 2, 139–145, (2014).
  1. Demongeot, J., Laksaci, A., Madani, F. Rachdi, M. Functional data: Local linear estimation of the conditional density and its application, Statistics, 47, pp. 26-44 (2013).
  2. Gheriballah, A. Laksaci and S. Sekkal Nonparametric M-regression for functional ergodic Stat. Probab . Lett 83, 902-908, (2013).
  3. S. Dabo-Niang, Z. Kaid and A. Laksaci Spatial conditional quantile regression: Weak consistency of a kernel estimate Revue Roumaine de Mathématique Pures et Appliquées (accepted) .
  4. S. Dabo-Niang, Z. Kaid and A. Laksaci Asymptotic properties of the kernel estimate of the spatial conditional mode when the regressor is functional (en révision ).
  5. Laksaci A. and B. Mechab Conditional hazard estimate for functional random fields (en révision).
  6. F. Benziadi A. Laksaci, and F. Tebboune Recursive kernel estimate of the conditional quantile for functional ergodic data, (en révision).
  7. M. Rachdi, A. Laksaci, J. Demongeot, A. Abdali and F.Madani. Theoretical and practical aspects on the quadratic error in the local linear estimation of the conditional density for functional data, (en révision).
  8. A. Laksaci, S. Rahmaani and Rachdi Spatial modelization : local linear estimation of conditional distribution for functional data.Spatial Statistics, 6, 1-23, (2013)
  9. A. Laksaci, F. Madani and M. Rachdi. Kernel conditional density estimation when the regressor is valued in a semi-metric space ,Comm. Statist. Theory and Methods, 42,3544-3570, (2013).
  1. M.K. Attouch, Z. Chikr El Mezouar, M. Gabr. Linear Regression with Bilinear Time Series Errors. PanAmerican Mathematical Journal, 1, 1-13, 2012.
  2. M.K. Attouch, T. Benchik. Asymptotic distribution of robust k-nearest neighbour for functional nonparametricmodels.Matematicki Vesnik , 64, 275-285, 2012.
  3. Z. Chikr El Mezouar, M.K. Attouch. Using Iterative linear regression model to time seriesmodels. Electronic Journal of Applied Statistical Analysis, EJASA,N°2, Vol 5, 137-150, 2012.
  4. S. Dabo-Niang, Z. Kaid and A. Laksaci, Sur la régression par quantile pour variable explicative fonctionnelle: Cas des données spatiales C. R. Math. Acad. Sci. Paris 349, 1287-1291, (2012).
  5. S. Dabo-Niang and A. Laksaci, Functional quantile regression estimation: Application to functional times series prediction, Comm. Statist. Theory and Methods, 41 1254-1268, (2012).
  6. S. Dabo-Niang, Z. Kaid and A. Laksaci, On spatial conditional mode estimation for a functional regressor Stat. Probab . Lett. 82 ,1413-1421, (2012).
  7. Attouch M., Chouaf B. and Laksaci A. Nonparametric M-estimation for functional spatial data, communication of the Korean Statistical society, 19, 193-211, (2012).
  8. M. Attouch, A. Gheriballah and A. Laksaci Convergence Presque complète d´un estimateur robuste de la régression non paramétrique fonctionnelle: Cas spatial, Pub. Inst. Stat. Univ. Paris LI, Ann. I.S.U.P. 56 3-16, (2012).
  9. N. Hachemi and A. Laksaci, Estimation de la régression pour variable explicative et réponse fonctionnelles dépendantes, J. Probab. and Stat . Sci. 10, 153-160, (2012).
  10. F. Ferraty, A. Laksaci, A. Tadj, P. Vieu. Estimation de la régression pour variable explicative et réponse fonctionnelles dépendantes C. R. Math. Acad. Sci. Paris 350 no. 13-1430, (2012).
  11. A. Chouaf and Laksaci A. On the functional local linear estimate for spatial regression. Stat. Risk Model. 29 no. 3, 189–214 31, (2012).
  12. M. Attouch, A. Laksaci and E. Ould-Said Strong uniform convergence rate of a robust estimator of the regression function forfunctional and dependent processes, Journal of the japan statistical society,42, 125-143. (2012)
  1. M. Attaoui, S. A. Laksaci and E. Ould-Said A note on n the conditional density estimate in the single functional index mode Stat. Probab . Lett. 81 45-53, (2011).
  2. Ferraty, F., Laksaci, A., Tadj, A., Vieu. P., Kernel regression with functional response, Electronic Journal of Statistics, 5, 159-171, (2011).
  3. A. Laksaci, M. Lemdani and E. ould-said Asymptotic results for an $L^1$-norm kernel estimator of the conditional quantile for functional time series data, Sunkhya 37-A, 124-141, (2011).
  1. A. Laksaci and B. Mechab Estimation non-paramétrique de la fonction de hasard avec variable explicative fonctionnelle: Cas des données spatiales, Revue Roumaine de Mathématique Pures et Appliquées 55, 35-51 (2010).
  2. A.Gheriballah, A. Laksaci and R. Rouane. Robust nonparametric estimation for spatial regression, Journal of Statistical Planning and Inference, 140, 1656-1670 (2010).
  3. F. Ferraty, A. Tadj, A. Laksaci and P. Vieu Rate of uniform consistency for nonparametric estimates with functional variables, Journal of Statistical Planning and Inference, 140, 335-352, (2010).
  4. Demongeot, J., Laksaci, A., Madani, F. Rachdi, M. Estimation locale linéaire de la densité conditionnelle pour des données fonctionnelles. C. R. Math. Acad. Sci. Paris 348 , 931-934, (2010).
  5. M. Attouch, A. Laksaci and E. Ould-Said Asymptotic normality of a robust estimator of the regression function for functional time series data, Journal of the Korean Statistical Society, 39, 489-500, (2010).
  6. S. Dabo-Niang and A. Laksaci, Note on conditional mode estimation for functional dependent data, Statistica 70, 83-94, ( 2010).
  7. M. Attouch, A. Laksaci, E. Ould Said. Estimation non paramétrique robuste de la fonction de régression. Variables fonctionnelles. Editions Universitaires Européennes, 2010. ISBN: 978-613-1-50678-9.
  1. A. Laksaci, M. Lemdani and E. Ould-said A generalized L_1-approach for a kernel estimator of conditional quantile with functional regressors: Consistency and asymptotic normality, Stat. Probab . Lett. 79 ,1065-1073, (2009).
  2. M. Attouch, A. Laksaci and E. Ould-Said Asymptotic distribution of robust estimator for functional nonparametric modes, Comm. Statist. Theory and Methods, 38, 1317-1335, (2009).
  3. A. Laksaci and F. Maref Conditional cumulative distribution estimation and its applications, J. Probab. and Stat . Sci. 7 57-69, (2009).
  4. A. Laksaci and F. Maref Estimation non paramétrique de quantiles conditionnels pour des variables fonctionnelles spatialement dépendantes, C. R., Math., Acad. Sci. Paris 347, 17, 1075-1080 (2009).

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