Authors: Dette, Holger
Pepelyshev, Andrey
Zhigljavsy, Anatoly
Title: Best linear unbiased estimators in continuous time regression models
Language (ISO): en
Abstract: In this paper the problem of best linear unbiased estimation is investigated for continuous-time regression models. We prove several general statements concerning the explicit form of the best linear unbiased estimator (BLUE), in particular when the error process is a smooth process with one or several derivatives of the response process available for construction of the estimators. We derive the explicit form of the BLUE for many specific models including the cases of continuous autoregressive errors of order two and integrated error processes (such as integrated Brownian motion). The results are illustrated by several examples.
Subject Headings: linear regression
continuous autoregressive model
AR processes
optimal design
signed measures
correlated observations
Issue Date: 2016
Appears in Collections:Sonderforschungsbereich (SFB) 823

Files in This Item:
File Description SizeFormat 
DP_5816_SFB823_Dette_Pepelyshev_Zhigljavsky.pdfDNB494.23 kBAdobe PDFView/Open

This item is protected by original copyright

Items in Eldorado are protected by copyright, with all rights reserved, unless otherwise indicated.