Mustapha Rachdi' Home Page
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Publications


 Some books and recent publications (since 2010) in peer-reviewed journals


BOOKS:
  • M. Rachdi (Guest Editor, 2023).
    Functional Data Analysis: Theory and Applications to Different Scenarios
    Mathematics, an Open Access Journal by MDPI
    https://www.mdpi.com/journal/mathematics/special_issues/45POZ9BG9S


  • E. Ould-Said, I. Ouassou and M. Rachdi (Editors, 2013).
    Functional Statistics and Applications
    Contributions to Statistics, Springer. 




SUBMITTED MANUSCRIPTS:
  • M. Alahiane, ..., I. Ouassou and M. Rachdi (2023).
    On the Functional Projection Pursuit Regression for Generalized Partially Linear Single Index Model.

    Submitted manuscript.
  • M. Alahiane, ..., I. Ouassou and M. Rachdi (2023).
    FPPR-Generalized Partially Linear Single Index Model.

    Submitted manuscript. 
REVISED MANUSCRIPTS:
  • M.Boumahdi, A. Laksaci, I. Ouassou and M. Rachdi (2023).
    Conditional cumulative distribution function for surrogate scalar response
    .
    Metrika, Vol. , N. , pp. -. Doi: https://doi.org/
PUBLISHED & ACCEPTED PAPERS:
  • O. Litmein, A. Laksaci, L. Ait-Hennani, B. Mechab and  M. Rachdi (2023).
    Asymptotic normality of the local linear estimator of the functional expectile regression
    .
    Journal of Multivariate Analysis, Vol. , N. , pp. -. Doi: https://doi.org/10.1016/j.jmva.2023.105281
  • M. Boumahdi, I. Ouassou and  M. Rachdi (2023).
    Estimation in nonparametric functional-on-functional models with surrogate responses
    .
    Journal of Multivariate Analysis, Vol.198,  N. , pp. 105231. Doi:https://doi.org/10.1016/j.jmva.2023.105231
  • M. Boumahdi, I. Ouassou and  M. Rachdi (2023).
    Generalized regression function for surrogate scalar response
    .
    Mathematical Modeling and Computing, Vol. 10, N. 3, pp. 625-637. Doi: https://doi.org/10.23939/mmc2023.03.625
  • A. Azzi, A. Belguerna, A. laksaci and M. Rachdi (2023).
    The scalar-on-function modal regression for functional time series data
    .
    Journal of Nonparametric Statistics. Vol. , N.  , pp. -. Doi: https://doi.org/10.1080/10485252.2023.2233642
  • Z.C. El Mezouar, F. Aishahrani, I.M. Almanjahie, Z. Kaid, A. Laksaci and  M. Rachdi (2023).
    A scalar-on-function relative error regression for weak dependent case

    Axioms, Vol. 12, N. 7, pp. 613. Doi: https://doi.org/10.3390/axioms12070613
  • M. Boumahdi, I. Ouassou and  M. Rachdi (2023).
    Conditional density function for surrogate scalar response
    .
    Statistics in Transition New Series, Vol. 24, N. 3, pp. 117-138. Doi: https://doi.org/10.59170/stattrans-2023-039
  • L. Ait-Hennani, Z. Kaid, A. Laksaci and M. Rachdi (2022).
    Nonparametric estimation of the expected shortfall regression for quasi-associated functional data
    .
    Mathematics, Vol. 10, N. 23, pp. 4508. Doi: https://doi.org/10.3390/math10234508
  • M. Jellassi, K. Oshinubi, M. Rachdi and J. Demongeot (2022).
    Epidemic dynamics on social networks.
    AIMS Bioengineering, Vol. 9, N. 4, pp. 348-361. Doi: 10.3934/bioeng.2022025
  • F. Alshahrani, I. M. Almanjahie, Z. C. Elmezouar, Z. Kaid, A. Laksaci and  M. Rachdi (2022).
    Functional ergodic time series analysis using expectile regression.
    Mathematics, Vol. 10, N. 20, pp. 3919. Doi: https://doi.org/10.3390/math10203919
  • M. Alahiane, I. Ouassou, M. Rachdi and P. Vieu (2022).
    High dimensional statistics: Non-parametric generalized functional partially linear single-index model.
    Mathematics, Vol. 10, N. 15, pp. 2704. Doi: https://doi.org/10.3390/math10152704
  • F. Mokhtari, R. Rouane, S. Rahmani and  M. Rachdi  (2022).
    Consistency results of the M-regression function estimate for continuous time stationary and ergodic data
    STAT, Vol. 11, N. 1, pp. e484. Doi: 10.1002/STA4.484
  • O. Bouanani, M. Rachdi and S. Rahmani (2022).
    High dimensional statistics: Quadratic error in the local linear estimation of the relative regression
    Bulletin of the Institute of Mathematics Academia Sinica, Vol. 17, Issue 2, pp. 335-348, Doi: https://doi.org/10.21915/BIMAS.202220610.21915/BIMAS.2022206
  • O. Oshinubi, S. Buhamra, N.M. Al-Kandari, J. Waku, M. Rachdi and J. Demongeot (2022).
    Age dependent epidemic modelling of COVID-19 outbreak in Kuwait, France and Caeroon
    Healthcare, Vol. 10, Issue 3, pp. 482. Doi: https://doi.org/10.3390/healthcare10030482
  • M. Rachdi, A. Laksaci, N. M. Al-Kandari (2022).
    Expectile regression for spatial functional data (sFDA).

    Metrika, Vol. 85, pp 627
    -655 . Doi: 10.1007/s00184-021-00846-x
  • K. Oshinubi, M. Rachdi and J. Demongeot (2022)
    Modelling of Covid-19 pandemic vis-a-vis some socio-economic factors
    Front. Appl. Math. Stat., Vol. 7, pp 786983. Doi:10.3389/fams.2021.78698
  • M. Abujazar, S. Al-Awadhi, H. Bensmail and M. Rachdi (2022).
    Effect of temperature on the spread of COVID-19 in Qatar, Kuwait and other Gulf countries
    Kuwaitian Journal of Science. Doi:10.48https://doi.org/10.48129/KJS.SPLCOV.19499
  • I. Almanjahie, Z. Kaid, A. Laksaci and M. Rachdi (2022).
    Estimating the conditional density in scalar-on-function regression structure: k-N-N local linear approach
    Mathematics, Vol. 10, Issue 6, pp. 902. Doi: https://doi.org/10.3390/math10060902
  • K. Oshinubi, F. Ibrahim, M. Rachdi and J. Demongeot (2022).
    Functional Data Analysis: Application to daily observation of COVID-10 prevalence in France
    AIMS Mathematics, Vol. 7, Issue 4, pp: 5347-5385. Doi: 10.3934/math.2022298
  • K. Oshinubi, A. Amakor, O. Peter, M. Rachdi and J. Demongeot (2022)
    Aproach to COVID-19 time series data using deep learning and spectral analysis methods
    AIMS Bioengineering (available on medRxiv), Vol. 9, Issue 1, pp 1-21. Doi:10.3934/bioeng.2022002
  • K. Oshinubi, F. Al-Awadhi, M. Rachdi and J. Demongeot (2021)
    Data analysis and forecasting of COVID-19 pandemis in Kuwait
    Kuwaitian Journal of Science (available on medRxiv). Doi: https://doi.org/10.48129/KJS.SPLCOV.14501
  • J. Demongeot, K. Oshinubi, M. Rachdi, H. Seligman, F. Thuderoz and Jules Waku (2021).
    Estimation of daily reproduction numbers in Covid-19 outbreak.
    Computation
    , Vol. 9, Issue 109. Doi:https://doi.org/10.3390/computation9100109
  • J. Demongeot, K. Oshinubi, M. Rachdi, L. Hobbad, M. Alahiane, S. Iggui, J. Gaudart, I. Ouassou (2021).
    The application of ARIMA model to analyze Covid-19 incidence pattern in several countries
    Journal of Mathematics and Computer Sciences (JMCS)
    , Vol.12, Issue 10, pp 1-23 - Doi: https://doi.org/10.28919/jmcs/6541

  • M. Alahiane, I. Ouassou, M. Rachdi and P. Vieu (2021)
    Generalized partially linear single-index models for functional data (GFPLSIM)
    Stats/MDPI, Vol. 4, Issue 4, pp  793-813.
  • K. Oshinubi, M. Rachdi and J. Demongeot (2021)
    Analysis of daily reproduction rates of COVID-19 using current health expenditure as gross domestic product percentage (CHE/GDP) across countries
    Healthcare, Vol. 9, Issue 1247. Doi: https://doi.org/10.3390/healthcare9101247
  • A. Laksaci, Z. Kaid, M. Alahiane, I. Ouassou, M. Rachdi (2021).
    Nonparametric estimations of the conditional density and mode when the regressor and the response are curves.
    Comm. Statist. Theory Meth., Vol. , Issue , pp  -. Doi: 10.1080/03610926.2021.1998831
  • A.M. Almanjahie, Z. Kaid,  A. Laksaci and M. Rachdi (2021).
    Predicting the temperature curve based on the fast kNN local linear estimation of the conditional distribution function
    PeerJ,
    Vol. 9:e11719
  • N. Sallahi, H. Park, F. El Mellouhi, M. Rachdi, I. Ouassou, S. Belhaouari, A. Arredouani and H. Bensmail (2021).
    Using unstated cases to correct for COVID-19 pandemic outbreak and its impact on easing the intervention for Qatar.
    Biology, Vol. 10, Issue 6,  pp 463.
    https://doi.org/10.3390/biology10060463 - 24 May 2021
  • A.M. Almanjahie, W.M. Alahmari, A. Laksaci, M. Rachdi (2021).
    Computational aspects of the kNN local linear smoothing for some conditional models in high dimensional statistics.
    Comm. Statist. Simul. Comput. Vol. , Issue , Pages -. 
    doi: 10.1080/03610918.2021.1923745
  • M. Rachdi,  A. Laksaci, A. Hamié, J. Demongeot and I. Ouassou (2021).
    Curves classification by using a local likelihood function and its practical usefulness for real data.
    Frontiers in Artificial Intelligence and Applications, Vol. 331, Pages 113-124.
    doi: 10.3233/FAIA299691
  • A.M. Almanjahie, Z.C. Elmezouar, A. Laksaci and M. Rachdi (2021).
    Smooth kNN local estimation of the conditional distribution function

    Mathematics, Vol. 9,  Issue 10, pp 1102. doi:10.3390/math9101102
  • A. Laksaci, E. Ould-Said, M. Rachdi (2021).
    Uniform consistency in number of neighbors of the kNN estimator of the conditional quantile model
    Metrika, Vol. 84,  pp 895-911.
    doi: https://doi.org/10.1007/s00184-021-00806-5
  • M. Rachdi, A. Laksaci, F. Al-Awhadi (2021).
    Parametric and nonparametric conditional quantile regression modelisation for dependent spatial functional data
    Spat. Statist., Vol. 43,  pp 100498.
    doi: 10.1016/j.spasta.2021.100498
  • M. Rachdi, A. Laksaci, Z. Kaid, A. Benchiha and F. Al-Awadhi (2021).
    kNN local linear regression for functional and missing data at random.
    Statistica Neerlandica, Vol. 75, Issue 1, pp 42-65. https://doi.org/10.1111/stan.12224
  • M. Rachdi, H. Bensmail, N.-M. Al-Kandari, I. Ouassou (2021).
    Heteroscedasticity Testing in Nonparametric Functional Data Statistics.
    International Journal of Applied Mathematics and Statistics, Vol. 22, Issue 1, pp 95-114.
  • H. Seligmann, S. Iggui, M. Rachdi, N. Vuillerme, J. Demongeot (2020).
    Inverted covariate effects for first versus mutated 2nd wave Covid-19: high temperature spread biased for young
    Biology, Vol. 9, Issue 8, pp 226 -. doi: 10.3390/biology9080226
  • M. Rachdi, M. Alahiane, I. Ouassou and P. Vieu (2020).
    Generalized functional partially linear single-index models.
    In book: Functional and High-Dimensional Statistics and Related Fields, pp 221-228. DOI: 10.1007/978-3-030-47756-1_29
  • M. Rachdi, J. Waku, H. Hazgui and J. Demongeot (2020).
    Entropy as a Robustness Marker in Genetic Regulatory Networks.
    Entropy, Vol. 22, Issue 3, Pages 260. DOI: 10.3390/e22030260, License CC BY
  • M. Rachdi, A. Laksaci, A.M. Almanjahie and Z.C. Elmezouar (2020).
    FDA: Theoretical and practical efficiency of the local linear estimation based on the kNN smoothing of the conditional distribution when there are missing data.
    Journal of Statistical Computation and Simulation, Vol. 90, Issue 8, Pages 1479-1495. DOI: 10.1080/00949655.2020.1732378
  • F. Ibrahim, A.H. Hassan, J. Demongeot, M. Rachdi (2020).
    Regression model for surrogate data in high dimensional statistics.

    Comm. Statist. Theory Methods, Vol. 49, Issue 13, Pages 3206-3227.  DOI:https://doi.org/10.1080/03610926.2019.158694

  •  O. Bouanani, S. Rahmani, A. Laksaci, M. Rachdi (2020).
    Asymptotic normality of conditional mode estimator for functional dependent data

    Indian Journal of Pure and Applied Mathematics, Vol. 51, Pages 465-481.

  • A.M. Almanjahie, Z.C. Elmezouar, A. Laksaci, M. Rachdi (2019).
    FDA: strong consistency of the kNN local linear estimation of the functional conditional density and mode.
    Journal of Nonparametric Statistics. Vol. 31, Issue 1, Pages 175-195. 
    DOI: 10.1080/10485252.2018.1538450
  • F. Awadhi, Z. Kaid, A. Laksaci, I. Ouassou, M. Rachdi (2019).
    Functional data analysis: local linear estimation of the  L1-conditional quantiles. 
    Statistical Methods & Applications,  Vol. 28, Issue 2, Pages 217-240. 
    DOI: 10.1007/s10260-018-00447-5
  • B. Altendji, J. Demongeot, A. Laksaci, M. Rachdi (2018).
    Functional Data Analysis: Estimation of the relative error in functional regression under random left-truncation.
    Journal of Nonparametric Statistics, Vol. 30, Issue 2, Pages 472-490.  
    https://doi.org/10.1080/10485252.2018.1438609
  • A.M. Almanjahie, Z.C. Elmezouar, A. Laksaci, M. Rachdi (2018).
    kNN local linear estimation of the conditional cumulative function: Dependent functional data case
    C. R. Acad. Sci. Paris, Mathématiques, Sér. I, Vol. 356, Issue 10, Pages 1036-1039. 
    DOI: 10.1016/j.crma.2018.09.001
  • M. Singull, M. Rachdi and G.S. Lo (2018).
    Editorial Paper of the Special Issue 13(1) of Afrika Statistika on Selected papers presented to EACSAM 2017.
    Afr. Stat., Vol. 13, Issue 1, Pages 1495-1497. DOI: 10.16929/as/1465.115 
  • O. Bouanane, A. Laksaci, M. Rachdi and S. Rahmani (2018).
    Asymptotic normality of some conditional nonparametric functional parameters in high-dimensional statistics.
    Behaviormetrika, Vol. 46, Issue 1, Pages 199-233.
    DOI: 10.1007/s41237-018-0057-9
  • A. Henien, L. Ait-Hennani, A. Laksaci, J. Demongeot, M. Rachdi (2018).
    Test d'hétéroscédasticité quand les covariables sont fonctionnelles
    C. R. Acad. Sci. Paris, Mathématiques, Sér. I, Vol. 356, Pages 571-574. 
    https://doi.org/10.1016/j.crma.2018.02.010 
  • L. Kara-Zaitri, A. Laksaci, M. Rachdi and P. Vieu (2017).
    Uniform in bandwidth consistency results for various kernel estimators involving functional data
    Journal of Nonparametric Statistics, Vol. 29, Issue 1, Pages 85-107.
  • K. Benhenni, S. Hedli-Griche and and M. Rachdi (2017).
    Regression models with correlated errors based on functional random design
    TEST, Vol. 26, Issue 1, Pages 1-21.
  • L. Kara-Zaitri, A. Laksaci, M. Rachdi and P. Vieu (2017).
    Uniform in the smoothing parameter consistency results in functional regression.
    In Functional Statistics and Related Fields, Edited by G. Aneiros, E. Bongiorno, R. Cao and P. Vieu
  • J. Demongeot, A. Laksaci, A. Naceri and M. Rachdi (2017).
    Local linear regression modelization when all variables are curves
    Statistics & Probability Letters, Vol. 121, Pages 37-44.
  • L. Kara-Zaitri, A. Laksaci, M. Rachdi and P. Vieu (2017).
    Data-driven kNN estimation for various problems involving functional data.
    Journal of Multivariate Analysis, Vol. 153, Pages 176-188.
  • J. Demongeot, A. Laksaci, A. Naceri and M. Rachdi (2016).
    Estimation locale linéaire de la fonction de régression pour des variables hilbertiennes
    C. R. Mathématiques, Vol. 354, Issue 8, Pages 847-850.
  • J. Demongeot, A. Hamié, O. Hansen and M. Rachdi (2015).
    Dynalets: A new tool for biological signal processing
    Functional Statistics and Applications, Part of the series Contributions to Statistics edited by Elias Ould-Said, Idir Ouassou and Mustapha Rachdi , 01/2015: Chapter pages 141-150; Springer International Publishing.
    ISBN:978-3-319-22476-3. 
  • J. Demongeot, M. Ghassani, H. Hazgui and M. Rachdi (2015).
    Demography in epidemics modelling: the copula approach
    Functional Statistics and Applications, Part of the series Contributions to Statistics edited by Elias Ould-Said, Idir Ouassou and Mustapha Rachdi , 01/2015: Chapter pages 151-161; Springer International Publishing.
    ISBN:978-3-319-22476-3. 
  • A. Naceri, A. Laksaci and M. Rachdi (2015).
    Exact quadratique error of the local linear regression operator estimator for functional covariates.
    Functional Statistics & Applications, Edited by E. Ould-Saïd, I. Ouassou and M. Rachdi, 01/2015: chapter Part of the series Contributions to Statistics. Pages 79-90; Springer International Publishing., ISBN: 978-3-319-22476-3
  • J. Demongeot, G.G. Carminati, F. Carminati  and M. Rachdi (2015).
    Stochastic monotony signature and biomedical applications
    C.R. Biologie, Vol. 338, Issue 12, Pages 777-783.
  • F. Messaci, N. Nemouchi, I. Ouassou and M. Rachdi (2015).
    Local polynomial modelling of the conditional quantile for functional data
    Statistical Methods & Applications, Vol. 29, Issue 1, Pages 597-622.
  • J. Demongeot, A. Hamié, A. Laksaci and M. Rachdi (2015).
    Relative-error prediction in nonparametric functional statistics: theory and practice
    Journal of Multivariate Analysis, Vol. 146, Pages 261-268.
  • J. Demongeot, A. Laksaci,  M. Rachdi and S. Rahmani (2014).
    On the local linear modelization of the conditional distribution for functional data 
    Sankhyä A: The indian journal of statistics, Vol. 76, Issue 2, Pages 328-355.
  • M. Rachdi, A. Laksaci, J. Demongeot, A. Abdali and F. Madani (2014).
    Theoretical and practical aspects on the quadratique error in the local linear estimation of the conditional density for functional 
    Computational Statistics & Data Analysis, Vol. 73, Issue 2, Pages 53-68.
  • I. Ouassou and M. Rachdi (2013).
    Quadratic loss estimation of a location parameter when a subset of its components is unknown
    Afr. Stat., Vol. 8, Pages 575-586.
  • A. Laksaci, M. Rachdi and S. Rahmani  (2013).
    Spatial modelization: local linear estimation of the conditional distribution for functional data 
    Spatial Statistics, Vol. 6, Pages 1-23.
  • J. Demongeot, M. Ghassani, I. Ouassou, C. Taramasco and M. Rachdi (2013).
    Archimedean copula and contagion modelling in epidemiology
    Networks and Heterogeneous Media, American Institute of Mathematical Science (AIMS), Vol. 08, Issue 01, Pages 149-170.
  • J. Demongeot, O. Hansen, A.S. Jannot, J. Mintsa, I. Ouassou, C. Taramasco and M. Rachdi (2013).
    Random modelling of contagious diseases
    Acta Biotheoretica, Vol. 61, Issue 01, Pages 141-172.
  • J. Demongeot, A. Laksaci, F. Madani and M. Rachdi (2013).
    Functional data: local linear estimation of the conditional density and its application
    Statistics, Vol. 47, Issue 01, Pages 26-44.
  • K. Benhenni, M. Rachdi and Y. Su (2013). 
    The effect of the regularity of the error process on the performance of kernel regression estimators.
    Metrika, 2012, vol. 76, issue 6, Pages 765-781.
  • A. Laksaci, F. Madani and M. Rachdi (2013). 
    Kernel conditional density estimation when the regressor is valued in a semi-metric space.
    Communications in Statistics-Theory and Methods, 2013, Volume 42, Issue 19, Pages 3544-3570.
  • I. Ouassou and M. Rachdi (2012). 
    Regression operator estimation by delta-sequences method for functional data and its applications.
    AStA Advances in Statistical Analysis, 2012, vol. 96, Pages 451-465. DOI: 10.1007/s10182-011-0175-0
  • J. Demongeot, J. Gaudart, J. Mintsa and M. Rachdi (2012).
    Demography in epidemics modelling.
    Communications on Pure and Applied Analysis, Volume 11, Issue 01, 2012, Pages 61-82.
  • J. Demongeot, J. Gaudart, A. Lontos, J. Mintsa, E. Promayon and M. Rachdi (2011). 
    Zero-diffusion domains in reaction-diffusion morphogenetic & epidemiologic processes. 
    International Journal of Bifurcation and Chaos, 2012, Volume 22, Issue 2, Pages 1250028_1-23. DOI: 10.1142/S0218127412500289.
  • S. Dabo-Niang, M. Rachdi and A.-F. Yao (2011). 
    Kernel regression estimation for spatial functional random variables.
    Far East Journal of Theoretical Statistics, Volume 37, Issue 02, Pages 77-113.
  • I. Ouassou et M. Rachdi (2011). 
    Quadratic loss estimation of a location parameter when a subset of its components is nonegative.
    C. R. Acad. Sci. Paris, Sér. I, Volume 349, Issues 17-18, September 2011, Pages 995-998.
  • J. Demongeot, A. Laksaci, F. Madani and M. Rachdi (2011).
    A fast functional locally modeled conditional density and mode for functional time-series.
    Recent Advances in Functional Data Analysis and Related Topics, Contributions to Statistics, 2011, 
    Pages 85-90, DOI: 10.1007/978-3-7908-2736-1_13, Physica-Verlag/Springer.
  • J. Demongeot, J. Mintsa and M. Rachdi (2011).
    Stochastic approach in modelling epidemic spread.
    IEEE Advanced Information Networking and Application, Pages 478-482, 2011, DOI: 10.1109/WAINA.2011.153.
  • M. El Methni and M. Rachdi (2011).
    Local weighted average estimation of the regression operator for functional data.
    Communications in Statistics - Theory and Methods, Volume 40, Issue 17, Pages 3141-3153.
  • J. Demongeot, A. Laksaci, F. Madani and M. Rachdi (2010).
    Estimation locale linéaire de la densité conditionnelle pour des données fonctionnelles. 
    C. R. Acad. Sci. Paris, Sér. I, 348, No. 15-16, Pages 931-934.
  • J. Gaudart, M. Ghassani, J. Mintsa, M. Rachdi, J. Waku and J. Demongeot (2010).
    Demography and Diffusion in epidemics: Malaria and Black Death spread.
    Acta Biotheoretica, Volume 58, No. 2-3, Pages 277-305.
  • J. Gaudart, M. Ghassani, J. Mintsa, M. Rachdi, J. Waku, O.K. Doumbo and J. Demongeot (2010).
    Demographic and spatial factors as causes of an epidemic spread, the copula approach. Application to the retro-prediction of the Black Death epidemy of 1346. 
    IEEE Advanced Information Networking and Application, DOI 10.1109/WAINA.2010.79, Pages 751-758.
  • K. Benhenni, S. Hedli-Griche and M. Rachdi (2010).
    Estimation of the regression operator from functional fixed-design with correlated errors.
    Journal of Multivariate Analysis, Volume 101, No. 02, Pages 476--490.
  • I. Ouassou and M. Rachdi (2010).
    Stein type estimation of the regression operator for functional data.
    Advances and Applications in Statistical Sciences, Volume 01, No. 2, Pages 233-25
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