On the nonparametric estimation of the functional regression based on censored data under strong mixing condition

In this paper, we are concerned with local linear nonparametric estimation of the regression function in the censorship model when the covariates take values in a semimetric space. Then, we establish the pointwise almost-complete convergence, with rate, of the proposed estimator when the sample is a strong mixing sequence. To lend further support to our theoretical results, a simulation study is carried out to illustrate the good accuracy of the studied method.