Functional data often arise in the areas where the causal treatment effect is of interest.
However, research concerning the effect of a functional variable on an outcome is typically …

In this article, we propose a novel estimator of extreme conditional quantiles in partial
functional linear regression models with heavy‐tailed distributions. The conventional …

This article introduces a high-dimensional linear IV regression for the data sampled at mixed
frequencies. We show that the high-dimensional slope parameter of a high-frequency …

Statistical inference for function-on-function linear regression Page 1 Bernoulli 30(1), 2024,
304–331 https://doi.org/10.3150/23-BEJ1598 Statistical inference for function-on-function …

This paper extends the linearized maximum rank correlation (LMRC) estimation proposed
by Shen et al.(2023) to the setting where the covariate is a function. However, this extension …

Confidence bands are used to estimate the likely range of the true parameter, whereas
prediction bands provide an idea of the possible values of the parameter after applying a …

In this paper, we propose a functional partially linear regression model with latent group
structures to accommodate the heterogeneous relationship between a scalar response and …

In this paper, we consider the linear regression model Y= SX+ ε with functional regressors
and responses. We develop new inference tools to quantify deviations of the true slope S …

In this paper, we consider the estimation and inference in partially functional linear
regression with multiple functional covariates. We estimate the parameters and the slope …

In the last decades, new branches of statistical research have developed to meet the needs
of an economy with growing data volumes at its disposal. One approach to analyze large …