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arXiv · 1902.08590

Parameter estimation for random sampled Regression Model with Long Memory Noise

Héctor Araya·Natalia Bahamonde·Lisandro Fermín·Tania Roa·Soledad Torres
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Abstract

In this article, we present the least squares estimator for the drift parameter in a linear regression model driven by the increment of a fractional Brownian motion sampled at random times. For two different random times, Jittered and renewal process sampling, consistency of the estimator is proven. A simulation study is provided to illustrate the performance of the estimator under different values of the Hurst parameter H.

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Héctor Araya, Natalia Bahamonde, Lisandro Fermín, Tania Roa, Soledad Torres. 2019-02-22. Parameter estimation for random sampled Regression Model with Long Memory Noise. https://arxiv.org/abs/1902.08590

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