Authors: Dette, Holger
Pepelyshev, Andrey
Zhigljavsky, Anatoly
Title: Optimal designs for regression models with autoregressive errors structure
Language (ISO): en
Abstract: In the one-parameter regression model with AR(1) and AR(2) errors we find explicit expressions and a continuous approximation of the optimal discrete design for the signed least square estimator. The results are used to derive the optimal variance of the best linear estimator in the continuous time model and to construct efficient estimators and corresponding optimal designs for finite samples. The resulting procedure (estimator and design) provides nearly the same efficiency as the weighted least squares and its variance is close to the optimal variance in the continuous time model. The results are illustrated by several examples demonstrating the feasibility of our approach.
Subject Headings: linear regression
continuous autoregressive model
AR processes
optimal design
signed measures
correlated observations
Issue Date: 2016
Appears in Collections:Sonderforschungsbereich (SFB) 823

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