Siberian Federal University 
- Issue
- Journal of Siberian Federal University. Mathematics & Physics. 2020 13 (4)
- Authors
- Boudada, Halima; Leulmi, Sara; Kharfouch, Soumia
- Contact information
- Boudada, Halima: University Freres Mentouri Constantine 1, Algeria; ; Leulmi, Sara: LAMASD Laboratory University Freres Mentouri Constantine 1, Algeria; ; Kharfouch, Soumia: University Salah Boubnider Constantine 3, Algeria;
- Keywords
- functional data; truncated data; almost sure convergence; local linear estimator
- Abstract
In this paper, a nonparametric estimation of a generalized regression function is proposed. The real response random variable (r.v.) is subject to left-truncation by another r.v. while the covariate takes its values in an infinite dimensional space. Under standard assumptions, the pointwise and the uniform almost sure convergences, of the proposed estimator, are established
- Pages
- 480–491
- DOI
- 10.17516/1997-1397-2020-13-4-480-491
- Paper at repository of SibFU
- https://elib.sfu-kras.ru/handle/2311/135356
Journal of Siberian Federal University. Mathematics & Physics / Rate of the Almost Sure Convergence of a Generalized Regression Estimate Based on Truncated and Functional Data
Full text (.pdf)