The BLUE in continuous-time regression models with correlated errors
Holger Dette, Andrey Pepelyshev, Anatoly Zhigljavsky
The Annals of Statistics · 2019 · Volume 47 · Issue 4
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 on many examples.
Keywords
62M09, 62M10, AR processes, BLUE, continuous autoregressive model, correlated observations, Linear regression, optimal design, signed measures
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