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Optimal designs for regression models with autoregressive errors

Dette, Holger, Pepelyshev, Andrey ORCID: and Zhigljavsky, Anatoly ORCID: 2016. Optimal designs for regression models with autoregressive errors. Statistics and Probability Letters 116 , pp. 107-115. 10.1016/j.spl.2016.04.008

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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.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Mathematics
Subjects: Q Science > QA Mathematics
Additional Information: PDF uploaded in accordance with publisher's policies at (accessed 21.4.16).
Publisher: Elsevier
ISSN: 0167-7152
Date of First Compliant Deposit: 24 May 2017
Date of Acceptance: 15 April 2016
Last Modified: 06 Nov 2022 08:29

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