Year-end Sale % OFF 
Abstract
In this article, we study the fixed-design regression estimation based on real and artificial data, where the artificial data comes from previously undertaken similar experiments. A least-squares estimate that gives different weights to the real and artificial data is introduced. It is investigated under which condition the rate of convergence of this estimate is better than the rate of convergence of an ordinary least-squares estimate applied to the real data only. The results are illustrated using simulated and real data.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
