Robust estimation provides an alternative approach to classical methods, for instance, when
the data are affected by the presence of outliers. Recently, these robust estimators have …

This paper focuses on semi-functional partially linear regression model, where a scalar
response variable with missing at random is explained by a sum of an unknown linear …

We propose a family of robust nonparametric estimators for a regression function based on
the kernel method. We establish the asymptotic normality of the estimator under the …

In this paper, we investigate the relationship between a functional random covariable and a
scalar response which is subject to left-truncation by another random variable. Precisely, we …

In this paper, we investigate the estimation of conditional density function based on the
single-index model for functional time series data. The asymptotic normality of the …

Robust nonparametric equivariant M-estimators for the regression function have been
extensively studied when the covariates are in R k. In this paper, we derive strong uniform …

In this paper, the almost complete consistency and the asymptotic normality of the estimator
of the regression operator in the case of a censored response given a functional explanatory …

In this article we study a family of nonparametric estimators for the ψ-regression model when
the response variable is subject to left-truncation by another random variable. Under …

This paper is devoted to the study of asymptotic properties of the kernel estimator of the
robust regression function for stationary continuous‐time and ergodic data. Such a …

Let (T n) n≥ 1 be an independent and identically distributed (iid) sequence of interest
random variables (rv) distributed as T. In censorship models, T is subject to random …