Additive Regression Model for Continuous Time Processes

TL;DR

This paper develops an additive regression model for continuous time processes, establishing optimal convergence rates and error bounds using the marginal integration method.

Contribution

It introduces a new approach to additive regression for continuous time data, providing theoretical guarantees for estimation accuracy.

Findings

Established optimal uniform convergence rates.

Derived optimal asymptotic quadratic error.

Validated the effectiveness of the marginal integration method.

Abstract

In the setting of additive regression model for continuous time process, we establish the optimal uniform convergence rates and optimal asymptotic quadratic error of additive regression. To build our estimate, we use the marginal integration method.