Ibrahim M. Almanjahie^1,2,*, Omar Fetitah³, Mohammed Kadi Attouch³, Tawfik Benchikh^3,4

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6307-6319, 2023, DOI:10.32604/cmc.2023.033441

Abstract Functional statistics is a new technique for dealing with data that can be viewed as curves or images. Parallel to this approach, the Near-Infrared Reflectance (NIR) spectroscopy methodology has been used in modern chemistry as a rapid, low-cost, and exact means of assessing an object’s chemical properties. In this research, we investigate the quality of corn and cookie dough by analyzing the spectroscopic technique using certain cutting-edge statistical models. By analyzing spectral data and applying functional models to it, we could predict the chemical components of corn and cookie dough. Kernel Functional Classical Estimation (KFCE), Kernel Functional Quantile Estimation (KFQE),… More >

Ahmed Bachir^{1, *}, Ibrahim Mufrah Almanjahie^{1, 2}, Mohammed Kadi Attouch³

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2049-2064, 2020, DOI:10.32604/cmc.2020.011491

Abstract It is well known that the nonparametric estimation of the regression function is highly sensitive to the presence of even a small proportion of outliers in the data. To solve the problem of typical observations when the covariates of the nonparametric component are functional, the robust estimates for the regression parameter and regression operator are introduced. The main propose of the paper is to consider data-driven methods of selecting the number of neighbors in order to make the proposed processes fully automatic. We use the More >