The Estimating of the Conditional Density with Application to the Mode Function in Scalar-On-Function Regression Structure: Local Linear Approach with Missing at Random

Almanjahie, I., Kaid, Z., Laksaci, A., & Rachdi, M. (2022). Estimating the conditional density in scalar-on-function regression structure: k-N-N local linear approach.Mathematics, 10(6), 1-16. Search in Google Scholar

Attouch, M.., Bouabsa, W., & Chiker el Mozoaur, Z. (2018). The k-nearest neighbors estimation of the conditional mode for functional data under dependency. International Journal of Statistics & Economics, 19(1), 48-60. Search in Google Scholar

Attouch, M., & Bouabsa, W. (2013). Thek-nearest neighbors estimation of the conditional mode for functional data. Rev. Roumaine Math. Pures Appl., 58(4), 393-415. Search in Google Scholar

Attouch, M., Laksaci, A., & Messabihi, N. (2015). Nonparametric relative error regression for spatial random variables. Statistical Papers, 58(4), 987-1008. Search in Google Scholar

Amiri, A., Dabo-Niang, S., & Yahaya, M. (2016). Nonparametric recursive density estimation for spatial data. Comptes Rendus Math., 354, 205-210. Search in Google Scholar

Baìllo, A. & Grané, A. (2009). Local linear regression for functional predictor and scalar response. Journal of Multivariate Analysis, 100, 102-111. Search in Google Scholar

Barrientos-Marin, J., Ferraty, F., & Vieu, P. (2010). Locally modelled regression and functional data. Journal of Nonparametric Statistics, 22(5), 617-632. Search in Google Scholar

Boj, E., Delicado, P., & Fortiana, J. (2010). Distance-based local linear regression for functional predictors, Computational Statistics and Data Analysis, 54, 429-437. Search in Google Scholar

Chaouch, M., Laib, N., & Louani, D. (2014). Rate of uniform consistency for a class of mode regression on functional stationary ergodic data. Stat. Meth. Appl., 26, 19-47. Search in Google Scholar

Chahad, A., Aït-Hennani, L., & Laksaci, L. (2017). Functional local linear estimate for functional relative-error regression. Journal of Statistical Theory and Practice, 13(11), 771-789. Search in Google Scholar

Collomb, G., & Härdale, H. (1979). Strong uniform convergence rates in robust nonparametric time series analysis and prediction: Kernel regression estimation from dependent observations. Stochastic Processes and Their Application, 23, 77-89. Search in Google Scholar

Demongeot, J., Laksaci, A., Madani, F., & Rachdi, M. (2010). Local linear estimation of the conditional density for functional data. C. R., Math., Acad. Sci. Paris, 348, 931-934. Search in Google Scholar

Demongeot, J., Laksaci, A., Madani, F., & Rachdi, M. (2013). Functional data: local linear estimation of the conditional density and its application. Statistics, 47, 26-44. Search in Google Scholar

Ezzahrioui, M., & Ould-Said, E. (2006). On the asymptotic properties of a nonparametric estimator of the conditional mode for functional dependent data. Preprint, LMPA No 277, Univ. du Littoral Côte d’Opale. Search in Google Scholar

Fan, J. (1992). Design-adaptative nonparametric regression. Journal of the American Statistical Association, 87, 998-1004. Search in Google Scholar

Fan, J., & Gijbels, I. (1996). Local polynomial modelling and its applications. Chapman & Hall. Search in Google Scholar

Ferraty, F., Rabhi, A., & Vieu, P. (2008). Estimation non-paramétrique de la fonction de hasard avec variable explicative fonctionnelle. Revue de Mathématiques Pures et Appliquées, 53, 1-18. Search in Google Scholar

Ferraty, F., & Vieu, P. (2006). Nonparametric functional data analysis. Theory and practice. Springer-Verlag. Search in Google Scholar

Ferraty, F. (2010). High-dimensional data: a fascinating statistical challenge. J. Multivariariate Anal., 101, 305-306. Search in Google Scholar

Giraldo, R. Dabo-Niang S., & Martinez, S. (2018). Statistical modeling of spatial big data: an approach from a functional data analysis perspective. Statist. Probab. Lett., 136, 126-129. Search in Google Scholar

Hurber, P. (1964). Robust estimation of a location parameter. Ann. Math. Statist., 35, 73-101. Search in Google Scholar

Kirkby, J. L., Leitao, A., & Nguyen, D. (2021). Nonparametric density estimation and bandwidth selection with B-spline bases: a novel Galerkin method. Comput. Statist. Data Anal., 159. Search in Google Scholar

Laib, N., & Ouled-Said, E. (2000). A robust nonparametric estimation of the autoregression function under an ergodic hypothesis. Canad. J. Statist., 28, 817-828. Search in Google Scholar

Maillot, B., & Chesneau, C. (2021). On the conditional density estimation for continuous time processes with values functional in spaces. Statist. Probab. Lett., 178. Search in Google Scholar

Rachdi, M., Laksaci, A., Demongeot, J., Abdali, A., & Madani, F. (2014). Theoretical and practical aspects on the quadratic error in the local linear estimation of the conditional density for functional data. Computational Statistics & Data Analysis, 73, 53-68. Search in Google Scholar

Uspensky, J. V. (1937). Introduction to mathematical probability. Mc Graw-Hill. Search in Google Scholar

Zhou, Z., & Lin, Z. (2016). Asymptotic normality of locally modeled regression estimator for functional data. Journal of Nonparametric Statistics, 30(28), 116-131. Search in Google Scholar