Best linear unbiased estimators in continuous time regression models

Holger Dette; Andrey Pepelyshev; Anatoly Zhigljavsky

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arXiv · 1611.09804

Best linear unbiased estimators in continuous time regression models

Holger Dette·Andrey Pepelyshev·Anatoly Zhigljavsky

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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.

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Holger Dette, Andrey Pepelyshev, Anatoly Zhigljavsky. 2016-11-29. Best linear unbiased estimators in continuous time regression models. https://arxiv.org/abs/1611.09804

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