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A note on confidence intervals for parameter estimates of a spatio-temporal Ornstein-Uhlenbeck process
Michele Nguyen, Almut E. D. Veraart
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We compare two ways of constructing confidence intervals for the moments-matching parameter estimates of a Gaussian spatio-temporal Ornstein-Uhlenbeck process. It was found that those obtained via pairwise likelihood approximations had lower coverages and were more prone to the curse of dimensionality as opposed to those from a parametric bootstrap procedure.
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