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arXiv · 1603.09059

Maximum likelihood estimation for a bivariate Gaussian process under fixed domain asymptotics

Daira Velandia·François Bachoc·Moreno Bevilacqua·Xavier Gendre·Jean-Michel Loubes
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Abstract

We consider maximum likelihood estimation with data from a bivariate Gaussian process with a separable exponential covariance model under fixed domain asymptotic. We first characterize the equivalence of Gaussian measures under this model. Then consistency and asymptotic distribution for the microergodic parameters are established. A simulation study is presented in order to compare the finite sample behavior of the maximum likelihood estimator with the given asymptotic distribution.

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Daira Velandia, François Bachoc, Moreno Bevilacqua, Xavier Gendre, Jean-Michel Loubes. 2016-03-30. Maximum likelihood estimation for a bivariate Gaussian process under fixed domain asymptotics. https://arxiv.org/abs/1603.09059

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